Hyperautomation MSSP

Why MSSPs are Ditching Legacy SOAR for Hyperautomation

By Torq

August 5, 2025

7 Minute Read

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Managed security service providers (MSSPs), desperate to automate repetitive tasks, initially turned to SOAR to reduce their workload and improve threat response times.

But legacy SOAR still stalls at scale, struggles with multitenancy, and breaks on fast-moving APIs — so teams end up babysitting playbooks instead of stopping threats. That’s why leading MSSPs are switching to Torq Hyperautomation: event-driven and massively scalable, with agentless integrations,and no/low-code and AI-generated workflows that turn Tier-1 tasks into hands-off outcomes.

Where Legacy SOAR Breaks for MSSPs

Scalability issues: Legacy SOAR platforms don’t handle alert spikes well. When volumes surge, their schedulers queue work serially, pipelines back up, and response times slip. The result is delayed containment, missed SLAs, and a SOC that’s waiting on tooling instead of stopping threats.

Lack of true multitenancy: Most SOAR tools weren’t built to isolate tenants. A burst of noisy events for one customer can starve resources and slow playbooks for everyone else. For MSSPs running dozens of environments, that bleed-through turns one client incident into a cross-tenant performance hit.

Integration complexity: Connecting customer tools should be routine, but with legacy SOAR, it’s a big project. Custom connectors take weeks to build, break when APIs change, and demand ongoing care and feeding. Teams end up maintaining glue code or paying for professional services, burning time and margin that should go to defending customers.

High maintenance costs: Legacy SOAR products often come with high maintenance costs in terms of time and resources. An organization might use around 25 different playbooks for different services and integrations, each requiring regular updates and optimization. Before long you’re maintaining dozens of near-duplicates, versioning them, testing them, and fixing scripts after every platform update. The operational overhead snowballs and erodes profitability.

Limited customization and flexibility: SOAR stacks lock down scripting and libraries, which cap what you can actually build. If you can’t use common SDKs or craft custom logic, you’re stuck with canned steps that don’t match real-world workflows. Analysts spend more time working around the platform than improving outcomes.

Hyperautomation: Built for MSSP Scale

Legacy SOAR tools weren’t designed for the scale, complexity, and economics that MSSPs face today. They’re monolithic, brittle, and reliant on endless scripting to keep up with changing APIs and customer environments. As MSSPs grow, those limitations compound — onboarding slows down, SLA penalties mount, and gross margins erode. At Torq, we deemed SOAR dead, and industry analysts followed suit.

Security Hyperautomation is different. It’s event-driven, horizontally scalable, and built for multi-tenant operations from the ground up. Torq enables MSSPs to orchestrate real-time alerts and responses across dozens or hundreds of unique customer stacks.

Key advantages of Torq for MSSPs include:

Parallel execution: Torq runs thousands of workflows simultaneously, ensuring tenants never compete for capacity.
No-code/low-code and AI-built automation: Analysts can build, customize, and deploy workflows in hours — accelerating onboarding and reducing the need for engineering resources.
Limitless integrations: With 300+ native connectors and containerized options, Torq adapts to any toolset, no matter how fragmented or fast-changing.
AI-assisted efficiency: Torq’s AI SOC Analyst, Socrates, enriches, correlates, and classifies cases automatically, while analysts approve high-risk actions through Slack, Teams, or ITSM.

For MSSPs, this means Tier-1 cases can be fully automated, Tier-2 streamlined with supervised approvals, and Tier-3 supported with rich AI-driven context. The result: reduced MTTR, happier customers, and healthier margins — even as alert volumes and customer counts grow.

How MSSPs Use Torq Hyperautomation

Accelerating onboarding: Every new customer brings a unique stack of firewalls, EDRs, SaaS apps, and cloud platforms. Instead of writing one-off automation scripts, MSSPs use Torq’s template-first playbooks with tenant-specific variables and policy toggles. This lets them onboard new clients in hours or days — not weeks — while maintaining consistency across tenants.

Meeting SLAs: SLA exposure through missed MTTA or MTTR is a top MSSP pain point. With Torq, Tier-1 alerts are fully automated — phishing, commodity malware, suspicious logins, impossible travel — and higher-risk actions are gated for analyst approval in Slack or Teams. Every case is logged with timestamps and actions, making SLA reporting defensible and reducing penalties.

Handling integration complexity: Customers bring dozens of different tools, many with fast-changing APIs. Torq’s 300+ native integrations, containerized connectors, and no-code customization allow MSSPs to connect “anything to anything” without custom code. This flexibility reduces the integration maintenance tax that eats into MSSP margins.

Reducing analyst burnout: MSSPs often deal with massive alert queues across tenants. Torq automates over 90% of Tier-1 triage and enrichment, suppresses false positives, and prioritizes high-risk cases. Analysts spend less time on swivel-chair tasks and more on threat hunting and customer strategy.

Delivering continuous optimization: Clients expect not just coverage but ongoing improvement. Torq enables MSSPs to measure MTTR, suppression rate, and analyst touches per case across all tenants. Workflows can be tuned continuously, and reports are compliance-ready for SOC 2, NIST, HIPAA, or industry-specific audits.

The business impact for MSSPs: Faster onboarding (up to 18×), faster workflow creation (10×), automated handling of up to 95% of Tier-1 alerts, and more substantial gross margins per customer.

The MSSP Hyperautomation Playbook: How HWG Sababa Doubled SOC Output

A few years ago, Italy-based MSSP HWG Sababa faced a tipping point in its growth. Instead of trying to squeeze more efficiency out of scripts and manual processes, it rebuilt its SOC around Torq Hyperautomation™. The result was a complete step-change in scale and efficiency.

Within weeks of adopting Torq, HWG Sababa:

Automated 55% of monthly alerts by targeting repetitive Tier-1 cases first
Cut MTTI and MTTR by up to 95% for routine alerts and 85% for high-priority threats
Nearly doubled SOC productivity and capacity without adding headcount
Boosted analyst morale and retention by eliminating repetitive, burnout-inducing tasks
Reduced customer-side effort by automating remediation actions directly in client environments

Marco Fattorelli, Head of Innovation at HWG Sababa, said Torq enabled them to deliver automated threat detection, containment, and remediation inside customer environments, saving clients hours of manual effort while strengthening trust and satisfaction.

The takeaway is this: Hyperautomation isn’t just a technical upgrade for MSSPs — it’s a competitive differentiator. By combining no-code workflows, vendor-agnostic integrations, and AI-driven case management, MSSPs like HWG Sababa prove ROI instantly while building more scalable and sustainable SOCs.

“Based on customer feedback when we showcase our services, Torq is the ideal solution for adding value to our managed SOC, particularly with its seamless integrations. By accelerating our automations and responses, Torq Hyperautomation helps us stay ahead of the curve and the competition.”

– Marco Fattorelli, Head of Innovation, HWG Sababa

Join the World’s Top MSSPs in Ditching Legacy SOAR

Legacy SOAR can’t keep pace with the multi-tenant scale, SLA pressure, and tooling diversity MSSPs face every day. Hyperautomation fixes the foundation: elastic execution that never stalls during spikes, true tenant isolation, plug-anything integrations, and AI-assisted workflows that turn the Tier-1 grind into hands-off outcomes. That’s how managed security service providers protect margins while delivering faster MTTR, stronger SLAs, and happier analysts.

MSSPs worldwide use Torq Hyperautomation to stamp reusable playbooks across tenants, orchestrate any stack, capture audit-ready evidence by default, and gate high-risk actions through Slack/Teams.

Ready to trade scripting and an endless backlog for scalable, multi-tenant automation? Get the Managed Services Manifesto.

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Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

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The MSSP Hyperautomation Playbook: How HWG Sababa Doubled SOC Output

By Torq

July 29, 2025

4 Minute Read

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See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster.

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Most MSSPs know the drill: more clients, more tools, more alerts — and somehow, fewer people. The traditional playbook of hiring your way out or custom-scripting every integration just doesn’t work anymore. It’s slow and impossible to maintain across dozens of environments.

HWG Sababa — an Italy-based MSSP — realized this early. Rather than patching the same old processes, they tore up the traditional playbook and rebuilt their MSSP SOC with Hyperautomation as the foundation.

The Top 4 MSSP SOCs Challenges

Scaling security without scaling headcount: Manual processes and custom scripting don’t scale. MSSPs need fast, flexible, and repeatable security automation without needing to code every use case from scratch.
Supporting disjointed customer environments: Each customer brings their own security stack. Integrating dozens of SIEMs, EDRs, and threat intel tools quickly (and securely) is critical to onboarding and retention.
Keeping analysts productive and engaged: Burnout is real. If your SOC analysts are stuck in Tier-1 alert queues all day, you’ll lose them fast — and with them, your operational effectiveness.
Delivering and proving ROI: MSSPs must justify their value with quantifiable outcomes. Response speed, automation rates, and time savings matter just as much as detection quality.

Hyperautomation: The Solution to MSSP SOC Challenges

HWG Sababa, a leading Italian MSSP serving customers across Europe, the Middle East, and Central Asia, found themselves at a crossroads. Their custom-coded automation system had become a bottleneck — too slow and too dependent on developer resources.

To scale their SOC, they needed a new solution that was:

Easy for analysts to use; no specialized coding skills required
Fast to implement and scale across environments
Seamless to integrate with each customer’s existing security stack
Designed to eliminate repetitive manual tasks at every stage

They chose Torq Hyperautomation™. And the impact was immediate.

HWG Sababa: SOC Automation Results in Just Weeks

Automating 55% of Monthly Alerts

By focusing first on automating the repetitive, manual Tier-1 tasks that consumed analyst time, HWG Sababa rapidly automated over half (55%) of their total monthly alert volume.

Torq’s AI-driven enrichment and automated remediation reduced Mean Time to Investigate (MTTI) and Mean Time to Respond (MTTR) by 95% for low-to-medium-priority cases and by 85% for high-priority threats, enabling analysts to handle incidents in minutes rather than hours.

Productivity and Operational Capacity Nearly Doubled

Automating the heavy-lift processes immediately boosted MSSP SOC productivity and efficiency, effectively doubling the team’s operational capacity. SOC analysts moved away from repetitive tasks, shifting focus to complex and strategic cybersecurity analysis.

Enhanced Analyst Morale and Retention

Reducing repetitive workload drastically improved analyst engagement. Automating tasks with Torq freed their SOC analysts to focus on deeper, more strategic cybersecurity work, improving job satisfaction significantly.

Reduced Customer-Side Effort

HWG Sababa also used Torq to automate customer-side actions that previously required manual effort, dramatically reducing their clients’ workloads.

Marco Fattorelli, Head of Innovation, highlighted that Torq allowed HWG Sababa to deliver automated threat detection, containment, and remediation directly within their customers’ environments. This capability eliminated hours of manual effort for clients and significantly improved overall customer satisfaction.

Strategic Adoption Across the Organization

Torq quickly became a critical strategic tool for MSSP SOC operations and other departments. Teams across the organization began adopting Hyperautomation for their own workflows, leading to widespread efficiency gains. This cross-functional adoption underscores Torq’s usability and immediate, tangible benefits.

Hyperautomation: A Clear MSSP SOC Differentiator

Torq Hyperautomation has become a competitive differentiator for MSSPs across the world. Prospective customers immediately recognize the value of significantly reduced response times, precise alert handling, and quantifiable operational efficiency.

No-code/low-code workflows: Analysts — not just engineers — can own and evolve automations.
Vendor-agnostic integrations: Connect instantly with customer tech stacks, avoiding lock-in and delays.
AI-powered case management: Handle repetitive alerts automatically, while enriching and escalating what matters.
Quantifiable ROI: Track every automated action and turn it into clear business value, both for your SOC and your customers.

Looking Forward: A Hyperautomation-First Mindset

With Torq fully embedded into their operational DNA, MSSPs like HWG Sababa are able to evaluate every new tool, technology, or process first through the lens of automation. Hyperautomation isn’t just a technology choice — it’s central to a long-term operational strategy.

By moving away from manual scripting and legacy automation, MSSPs can dramatically increase their operational scale and responsiveness. Torq Hyperautomation transforms managed SOCs, doubles productivity, cuts response times to mere minutes, and delivers measurable value to MSSP customers.

The results for HWG Sababa speak for themselves: a stronger security posture, empowered analysts, happier customers, and a decisive competitive edge.

Ready to Scale Your MSSP SOC?

Torq helps MSSPs differentiate, accelerate, and deliver with unmatched speed and efficiency.

Want to see exactly how HWG Sababa scaled their MSSP SOC, doubled analyst productivity, and delivered measurable ROI with Torq?

Read the Case Study

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

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Integrations News & Events

Get AMP’d: Introducing the Torq Alliance & Momentum Partner Program

By Chris Coburn

July 29, 2025

4 Minute Read

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Chris Coburn is the Senior Director of Technology Alliances at Torq, where he leads strategic partnerships that fuel innovation and growth. With experience scaling alliance programs at cybersecurity leaders like Recorded Future, he brings an execution-first mindset to ecosystem development. He’s the architect of Torq’s AMP program, redefining how partners integrate, collaborate, and win together.

At Torq, we don’t believe in playing by the old rules. That’s why we’ve launched the Torq Alliance and Momentum Partners (AMP) program. It’s a bold new take on what a cybersecurity partnership can and should be. AMP is designed to accelerate SecOps innovation, eliminate red tape, and empower partners of all sizes to build, integrate, and grow.

We’re thrilled to welcome launch partners like Google Cloud Platform, Wiz, NVIDIA, Zscaler, Astrix, Intezer, Panther, Sweet Security, and more to the AMP ecosystem. Together, we’re building an alliance program that puts ideas, effort, and impact above everything else.

What Makes Torq AMP Different

Let’s be honest: most partner programs feel like gated clubs. Rigid tiers, “pay-to-play” models, and success metrics built for giants, not innovators.

With Torq AMP, there’s no tiering. No mandatory customer thresholds. No barriers to entry. What you build and how much effort you put into it matters. Whether you’re a two-person startup with a cool idea or an established leader reshaping a category, AMP gives you the tools and exposure to make it matter.

We’re looking for partners building the coolest, most impactful solutions and putting in the work to bring them to life.

Why Join AMP?

AMP is an ecosystem where innovation meets action. We’ve created a program that aligns technical creativity with meaningful business momentum, including:

Fast-track integration: You get your own Torq instance, hands-on support, and a clear path to go from concept to integration without unnecessary overhead.
Go-to-market that actually goes somewhere: From joint demos and field events to aligned sales plays and enablement, we work side-by-side to drive real pipeline.
Marketing with muscle: AMP partners tap into the full reach of the Torq brand, from strategic social promotion to presence in campaigns, solution briefs, the Torq platform, and yes, even custom swag.

And the best part? AMP is a living program. We don’t stop at launch. We keep building together — more use cases, content, and mutual value. The more you invest, the more you get back.

AMP in Action

Google Cloud + Torq: Powering Cloud-Scale Hyperautomation

Torq’s integration with AMP Partner Google Cloud Platform (GCP) empowers customers to build workflows across Gmail, Drive, Workspace, and more. Google Cloud and Torq accelerate processes with seamless orchestration, rapid threat detection, and automated remediation at scale, making it easier than ever for SecOps teams to protect their cloud environments.

Wiz + Torq: Accelerating Cloud Risk Response

Torq’s integration with Wiz enables cloud-native security teams to automate proactive risk management with ease. Through Torq AMP, joint customers can trigger workflows directly from Wiz alerts and use no-code automation to remediate vulnerabilities, update issue statuses, and correlate cloud risk data with broader security operations. Together, Torq and Wiz accelerate threat detection and response across complex multi-cloud environments.

Get AMP’d

Cybersecurity innovation doesn’t need more red tape; it needs more momentum. That’s exactly what Torq AMP delivers.

If you’re building technology that could transform how SOC teams work, we want to hear from you. Let’s build it, ship it, and wow our mutual customers — together.

Explore the Torq AMP program and get ready to integrate with the most-talked-about company in cybersecurity.

Apply for AMP

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

Get a Demo

Hyperautomation Security Engineering

Torq + SSDLC: Where Secure Automation Begins

By Torq

July 23, 2025

5 Minute Read

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See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster.

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Legacy SOAR solutions emerged in an era of traditional, static on-premises networks with fewer sophisticated threats. But today’s cybersecurity landscape is dramatically different — attack surfaces rapidly evolve, threats are multifaceted, and cybersecurity talent is increasingly scarce.

As organizations struggle with sprawling security stacks and burned-out SOC teams, legacy SOAR solutions reveal their significant limitations. One of the most critical weaknesses is their lack of support for the Secure Software Development Lifecycle (SSDLC).

The Evolution from SDLC to SSDLC

Every software application, from mobile apps to intricate enterprise solutions, follows a structured development process called the Software Development Lifecycle (SDLC). SDLC provides a systematic approach, covering requirement analysis, design, coding, testing, deployment, and maintenance. While it allows for systematic steps to ensure software quality and reliability, traditional SDLC often sidelines security until late stages in the software development process.

The growth of sophisticated cyber threats underscores the limitations of traditional SDLC. To address these gaps, the Secure Software Development Lifecycle emerged, embedding security practices at every stage of the development lifecycle. Unlike traditional SDLC, which prioritizes functionality and performance, SSDLC proactively addresses vulnerabilities and significantly reduces risk.

The Importance of Integrating SSDLC into Modern Development

Integrating SSDLC is essential for any organization serious about maintaining digital trust. Cyber threats continue to rise in complexity and frequency, making a security-first approach non-negotiable. The proactive, integrated model of SSDLC dramatically reduces vulnerability risks compared to traditional SDLC methods, which often rely on reactive, late-stage patching and inefficient security tests.

Transitioning to SSDLC signifies more than just a technical shift; it represents an organizational commitment to embedding security deeply into the culture and software development lifecycle, driving resilience, compliance, and long-term trust.

Where Legacy SOAR Fails: Lack of SSDLC Integration

SSDLC ensures that security considerations are seamlessly integrated throughout the entire software development lifecycle and automation workflows, reducing vulnerabilities before they become expensive, high-risk issues in production. However, legacy SOAR solutions typically:

Lack integrated tools and features specifically designed for SSDLC
Require substantial manual effort to verify that workflows meet security and compliance standards
Leave workflows vulnerable to potential security threats due to inadequate built-in security testing and checks

These gaps force organizations to invest considerable resources — both human and financial — to ensure automation workflows remain secure and compliant, resulting in higher operational costs and increased exposure to data breaches.

How Torq Hyperautomation Integrates SSDLC by Design

Unlike traditional SOAR solutions, Torq Hyperautomation™ inherently integrates SSDLC principles throughout its platform, ensuring security is embedded into every aspect of workflow development.

Built-in SSDLC Framework

Torq’s Hyperautomation platform offers a comprehensive framework that covers planning, software development, testing, deployment, and maintenance phases. Embedding secure software development into every step of automation ensures robust, compliant workflows.

Automated Testing and Continuous Validation

With Torq, rigorous automated testing is built into the workflow development process. These comprehensive tests check for:

Vulnerabilities: Continuous scanning and mitigation of security flaws.
Performance assessments: Ensuring security measures don’t degrade functionality.
Compliance adherence: Automatic checks aligned with industry standards and regulations.

Unlike legacy solutions, Torq’s automated tests are ongoing, not isolated to specific phases. This continuous validation ensures all workflow changes and updates remain secure and adhere strictly to best practices. Torq also integrates seamlessly with existing development tools, creating a unified and efficient workflow environment.

Environment Segmentation: Development, Staging, and Production

Torq allows security teams to separate workflow development into clearly defined staging and production environments. This enables controlled testing and refinement before workflows ever touch a live environment. By isolating workflows this way, Torq dramatically reduces the risk of security incidents and ensures smooth deployments.

Torq Hyperautomation also implements robust role-based access control (RBAC) by default. These stringent access controls ensure only authorized personnel can interact with specific functions, preserving workflow integrity and security.

Agile Workflow Development with Enhanced Security

Torq doesn’t just secure your automation workflows — it accelerates their development. Its intuitive, user-friendly interface empowers users of all technical skill levels to prototype, test, and refine workflows rapidly.

Torq’s iterative, agile-driven development process incorporates continuous feedback, ensuring automations remain effective and adaptive to evolving security requirements. This agile process far surpasses the capabilities of legacy SOAR platforms, enabling your organization to respond swiftly and confidently to new threats.

Hyperautomation is Essential for SSDLC

The future of software security demands an integrated, continuous SSDLC approach that seamlessly fits into an organization’s overall development strategy. Traditional SDLC approaches that defer security considerations are no longer viable in today’s rapidly evolving threat landscape.

Organizations adopting Torq’s Hyperautomation platform can confidently build security into the core of their development processes, ensuring their automation workflows remain robust and resilient against evolving threats. This continuous, integrated security approach positions organizations to maintain compliance, build digital trust, and sustainably mitigate risks.

Legacy SOAR solutions simply can’t keep up with modern cybersecurity demands. Their lack of built-in SSDLC support leaves critical gaps, resulting in higher costs, increased risks, and significant manual overhead. In contrast, Torq’s Hyperautomation platform is built from the ground up with security-first principles.

With automated SSDLC support, rigorous security checks, robust environment segmentation, and agile workflow development, Torq ensures automations are secure, compliant, and ready to handle today’s dynamic threat landscape.

Secure your organization’s future with Torq’s integrated SSDLC and Hyperautomation capabilities.

How to Migrate from SOAR to Torq

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

Get a Demo

AI Hyperautomation MSSP

The 5 Hidden Costs of SOAR for MSSPs — And What to Do Instead

By Torq

July 21, 2025

5 Minute Read

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See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster.

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Managed security is a margin game. MSSPs live under strict SLAs and relentless alert volume — usually without proportional headcount growth. Traditional SOAR promised relief, but at multi-tenant scale it often becomes a cost center.

Industry reality backs this up: 80% of security pros say legacy SOAR is too complex, costly, and time-consuming, 92% say it demands scripting skills, and 90% say it needs heavy up-front investment to build playbooks. Meanwhile, the average enterprise runs 76 security tools — and MSSPs are expected to integrate with all of them for every customer.

What’s the fix? A scalable security automation platform that consolidates enrichment, correlation, case management, and automated remediation. With Torq Hyperautomation, instead of pouring hours into brittle playbooks and manual triage, you can standardize cross-tenant workflows, automate Tier-1 at scale, and keep integrations healthy without constant rework. SLAs improve, analyst touches drop, and margins rise even as alert volume and tool sprawl grow.

Below, we expose five hidden SOAR costs that quietly erode MSSP margins and how Hyperautomation changes the economics from reactive and expensive to proactive and profitable.

Why Legacy SOAR Breaks MSSP Economics

Before we fix the margin math, we need to start by understanding why SOAR for MSSPs strains economics in the first place. Traditional SOAR platforms weren’t built for the scale and variability MSSPs face. Their monolithic architectures force every tenant to feel like a one-off deployment: custom environments, unique connectors, and per-client playbooks.

Growth means redeploying and maintaining entire stacks — not just scaling the parts that matter. This results in rising maintenance hours, higher change risk, surprise downtime, and shrinking gross margins per tenant.

If the operating model is the problem, the remedy is architectural. Enter Hyperautomation built for multi-tenant scale.

What Replaces SOAR: Hyperautomation for MSSPs

Torq Hyperautomation was built for MSSPs: multi-tenant by design, horizontally scalable, and event-driven. It delivers limitless integrations, intelligent case automation and prioritization, shared workflow libraries, and a team of AI Agents that can handle the grunt work. Tier-1 work is fully automated, Tier-2 becomes supervised (i.e. one-click approvals in chat), and high-risk actions stay human-in-the-loop — all with complete auditability.

The results are proven: 18× faster onboarding, 10× faster workflow creation, and up to 95% of Tier-1 alerts auto-investigated and enriched.

Most importantly, Hyperautomation shifts MSSP economics. With Torq, SOC leaders can directly track and improve MTTR/MTTA, alert suppression rates, analyst touches per case, onboarding hours per tenant, connector uptime, SLA credits, and gross margin per customer. The curves bend immediately: fewer manual touches, faster time-to-resolution, and consistently stronger SLA performance.

Let’s map how each hidden cost of SOAR shows up in the real world — and how Hyperautomation can fix it.

Hidden Cost #1: SLA Exposure and Penalties

SOAR was sold as “faster response,” yet MSSPs still juggle fragmented alerts, manual pivots, and rework. Every extra touch burns analyst time and risks SLA penalties. Missed MTTA/MTTR targets lead to SLA penalties and eroded customer trust, often caused by manual approvals and inconsistent response times.

How Torq helps: Resolution time is key to minimizing costly service penalties and increasing SOC efficiency. Torq automates Tier-1 triage, enrichment, and safe containment for everyday alerts — phishing, commodity malware, suspicious process trees, and impossible travel. Playbooks include timers, retries, and just-in-time approvals baked in, while every step and artifact is logged for defensible SLA reporting. MSSPs can quickly turn their top SLA pain points into automated flows that act instantly and escalate only when risk exceeds defined thresholds.

Hidden Cost #2: Legacy Security Environments

Every new tenant brings a unique blend of on-prem firewalls, legacy AV, multiple clouds, and niche SaaS. Onboarding devolves into endless script writing and one-off exceptions — “temporary” customizations become permanent snowflakes.

How Torq helps: Torq enables a template-first design approach, letting MSSPs build runbooks with tenant-specific variables and policy toggles. Hybrid connectivity options — from agentless APIs and secure tunnels to UI automation where APIs are missing — ensure MSSPs can onboard even the most complex tenant environments quickly and consistently.

Hidden Cost #3: Integration and Maintenance Tax

With SaaS security products multiplying, MSSPs struggle to keep integrations current, draining time and resources while limiting their ability to deliver baseline SOAR operations across global tenants.

How Torq helps: Torq’s native integrations, no-code customization, and containerized connectors eliminate integration bottlenecks. MSSPs can connect to virtually any system — internal or external — and scale orchestration across tenants without the ongoing integration tax of custom development and maintenance.

Hidden Cost #4: Alert Volume and Manual Triage

Scaling alert queues with more analysts is expensive and unsustainable. Relying on humans for every triage decision drags down ROI and creates inconsistent service delivery.

How Torq helps: Torq automates over 95% of Tier-1 alert handling, reducing manual workloads and slashing mean time to detect and respond. By eliminating repetitive triage tasks, MSSPs cut labor costs, improve gross margins, and give analysts space to focus on high-value investigations and customer needs.

Hidden Cost #5: Continuous Optimization and Reporting

Clients expect MSSPs not just to meet obligations, but to continually improve detection and response — while also delivering unified reporting across complex environments. This creates constant pressure to re-tune playbooks and validate workflows.

How Torq helps: Torq enables continuous optimization through Hyperautomation. MSSPs can orchestrate cross-tool workflows that evolve as client needs change, without requiring costly rebuilds or periodic manual evaluations. Reporting is built-in and mapped to compliance frameworks, giving clients the visibility they demand while reducing operational drag.

The Bottom Line for MSSPs

Legacy SOAR for MSSPs wasn’t built for today’s multi-tenant, API-driven, high-SLA reality. Its hidden costs show up as onboarding delays, brittle integrations, analyst burnout, and margin leakage you can’t explain away at QBRs.

Hyperautomation changes the SOC narrative: correlate once, enrich once, execute safely at scale, then repeat that win across every tenant without spawning “snowflake” workflows. The result is tighter MTTA/MTTR, fewer analyst touches per case, healthier SLA performance, and gross margins that improve as you grow, not the other way around.

Ready to retire SOAR and grow margin?

Get the Managed Services Manifesto

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

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AI Customers Hyperautomation

How Valvoline Hyperautomated Their SOC in Just One Week

By Brittney Wittfeldt

July 17, 2025

4 Minute Read

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Retail cybersecurity teams face a perfect storm: high-volume, low-signal alerts, a massive surface area across stores, POS systems, cloud apps, and third-party vendors, and an environment where any delay in response can lead to reputational and revenue damage.

Yet most retail SOCs are held back by aging infrastructure and brittle tools. Alert fatigue, false positives, and manual workflows turn shifts into chaos. Legacy SOARs aren’t helping; they’re often the problem.

To survive and scale, retail SOCs need automation that’s fast to deploy, easy to use, and flexible enough to handle diverse systems and real-world incident volume. That’s Torq Hyperautomation™. Valvoline faced these exact challenges — and overcame them — by replacing their brittle legacy SOAR with Torq, transforming their SOC in just one week.

Retail SOC Cybersecurity Challenges

Retailers handle massive volumes of customer data, making them prime targets for cybercriminals. At the same time, they face growing IT complexity across stores, e-commerce platforms, and third-party vendors. Legacy systems, minimal in-house resources, and constant alert fatigue make defending against modern threats increasingly difficult.

Top retail threats include:

Phishing and social engineering: Used to steal customer credentials or launch broader attacks.
Ransomware: Often triggered by phishing, disrupting business operations and demanding costly ransoms.
Third-party & IoT risks: Unsecured vendors and smart devices expand the attack surface dramatically.
Credential attacks: From fake accounts to credential stuffing, bots wreak havoc on authentication systems.
DDoS and web exploits: Automated attacks can bring down retail systems and erode customer trust.

To stay resilient, modern retail SOCs need security automation that neutralizes threats faster than attackers can exploit them, without increasing analyst burden.

Hyperautomation: A Better Way to Automate the Retail Industry

When Corey Kaemming became Senior Director of InfoSec at Valvoline, he inherited a challenge familiar to many security leaders: Legacy SOAR that broke more than it built. His SOC had been cut in half during a major divestiture, and their deeply customized, brittle SOAR couldn’t keep up. Only a few SMEs could operate it, and everyone else was blocked.

“We needed a platform that didn’t require hard-to-find coding skills. Our SOAR was slowing us down, not scaling us up,” Corey shared. What followed was a full transformation of Valvoline’s security operations — one powered by Torq Hyperautomation™ for automation in retail.

How Valvoline Hyperautomated Their SOC

Valvoline put Torq to the test in a head-to-head proof of value. Within 48 hours, they were live. Within a week, they were running real automation in production.

Their Rapid7 integration, which had stalled for hundreds of hours in their SOAR, was live in less than a week in Torq.
Phishing triage, once eating up to 12 hours per day, became a fully automated workflow, slashing workload by 6–7 analyst hours daily.
Containment actions — password resets, session terminations, and more — became automatic, logged, and auditable via Torq’s built-in case management.
Non-developers could use no-code/low-code drag-and-drop workflows, which made it easy for anyone on the team to contribute.

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”
Corey Kaemming, Senior Director of InfoSec at Valvoline

From Reactive to Proactive: The SOC of the Future

With Torq, retail companies like Valvoline can move from reactive response to a strategic focus.

Anyone can build: Drag-and-drop workflows let even non-developers create automation.
Analysts reclaim their time: Repetitive Tier-1 tasks became automated, eliminating alert fatigue.
Response becomes instant: Clicking a malicious link now triggers a fully automated incident response workflow — no manual intervention required.
Case management got smarter: Built-in automation tracks every action and provides rich incident metrics.

Why Retail SOCs Are Turning to Hyperautomation

Torq isn’t just a better product — it’s a better partner.

From onboarding to enablement, SOC teams are supported by a dedicated Customer Success Manager, Solutions Architect, and content resources at every step. And because Torq is built for scale, Valvoline is now expanding automation to adjacent teams like identity and fraud.

What once took weeks or months now takes days. The Valvoline team is delivering more value with fewer resources — and doing it without waiting on developers or vendors.

Torq Hyperautomation gave Valvoline the speed, flexibility, and confidence they needed to scale security without scaling burnout. Within 48 hours, they were live. Within a week, they were automated. And, they’re just getting started with all that they can do with Torq.

See how Valvoline replaced legacy SOAR, automated phishing triage, and transformed their retail SOC in just one week with Torq Hyperautomation.

Read the Case Study

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

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Research Security Automation 101

Security Operations Center Best Practices to Boost Security & Automate Smarter

By Patrick “PO” Orzechowski

July 16, 2025

10 Minute Read

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Torq Field CISO Patrick "PO" Orzechowski, SOC leader and expert

Patrick Orzechowski (also known as “PO”) is Torq’s former Field CISO, bringing his years of experience and expertise as a SOC leader to our customers. PO is a seasoned security veteran with a deep understanding of the modern security landscape. You can find him talking to SOC leaders and CISOs from major brands at cybersecurity events around the world.

Running a SOC isn’t for the faint of heart. I should know. Late nights, understaffed teams, endless alerts, and jumping from tool to tool — all fueled by a probably unhealthy amount of energy drinks? Yeah, I’ve been right there in the trenches. And let’s face it: the old SecOps playbooks can’t scale in the face of modern SOC challenges.

The SOC best practices below are the hard-won lessons that separate the security operations centers that struggle to keep up from the ones that position themselves as strategic value centers.

Level Up Your SOC: Best Practices to Stay Sharp and Secure

A Security Operations Center (SOC) brings together people, processes, and technology to manage and improve an organization’s security posture. Put simply, it’s the command center for protecting a business from cyber risk and threats.

In a world where a single data breach can cost millions, an efficient SOC isn’t a luxury — it’s a core business function. An effective security operations center can significantly reduce an organization’s risk by identifying, analyzing, and responding to cybersecurity incidents in near real-time, or better yet, finding and mitigating vulnerabilities before they ever become an incident.

When I ask security operations center leaders the “why” behind the way they built their SOC, most mention that it’s to:

Proactively prevent cybersecurity incidents by detecting and fixing vulnerabilities, security monitoring, and gathering threat intelligence on known threats.
Minimize the impact of data breaches by rapidly containing incidents and minimizing their impact on the organization.
Ensure business continuity by protecting critical assets and data so business operations can continue without interruption.

At the end of the day, all of these drive up to the ultimate goal of a SOC: reducing risk to the business.

5 Most Common SOC Challenges

If you run an SOC, these challenges probably keep you up at night. They’re not just headaches — they’re fundamental risks to your security posture.

1. Alert Fatigue

Alert fatigue is more than just “too many alerts” — it’s a soul-crushing onslaught of low-fidelity noise and false positives that buries the critical alerts that matter. While the cybersecurity industry is a bit of a broken record around alert fatigue, it doesn’t change the fact that most teams are still struggling with it — more than half of security teams say false positives are a huge problem, and nearly two-thirds are overwhelmed by sheer data volume. Alert fatigue burns out already stretched-thin SOC teams, delays threat detection and incident response, and increases the risk of missed threats.

2. Tool Overload

Too many security operation centers I see have sprawling security stacks of disconnected tools that don’t play nice. Security analysts waste precious time swiveling between different UIs and even writing clunky PowerShell or Python scripts to gather information, trying to solve a puzzle with pieces from different boxes.

3. Manual Processes

In 2025, there’s simply no need for human SOC analysts to be manually copy-pasting information from one tool to another to build a case. These repetitive, mind-numbing tasks are slow, prone to human error, and a complete waste of your team’s valuable expertise.

4. Talent Shortage

Finding and retaining top-tier security talent is brutally competitive. The shortage is real, and it means you can’t just throw more people at the problem (especially when budgets are lean). You have to make the team you have exponentially more effective. A crucial part of that is keeping your SOC analysts engaged — automating mundane tasks takes tedious work off their plates, which directly increases morale, boosts productivity, and gives your best talent a reason to stay.

5. Scalability Issues

The volume of data from cloud environments, SaaS applications, and distributed endpoints is exploding, and the security perimeter is larger than ever. A SOC built on manual processes and disjointed tools simply cannot scale to meet this demand. As your business operations — and your attack surface — grows, your security coverage will fall further and further behind unless you start automating.

6. The Ransomware Time-Bomb

Today, every organization of any size is a target for ransomware, and ransomware operators are moving at unprecedented speed, with a median time from initial breach to business-ending payload of less than 24 hours. This breakneck pace demands an immediate and flawless response that is nearly impossible to deliver with manual processes.

7 Security Operation Center Best Practices

Since I started at Torq, I’ve heard the same story from CISOs over and over — they’ve finally reached a tipping point with tech sprawl. They’re looking at unwieldy, expensive security stacks and asking the hard questions: Are these dozens of tools actually making us more secure, or are they just burning out our security analysts and our budget?

This is leading to a massive push for real SOC transformation. The smartest leaders I talk to are no longer content with running a reactive cost center that just cleans up messes. They’re determined to build a proactive, data-driven value center that anticipates cyber threats and demonstrates clear ROI, often by replacing ten disjointed tools with three or four that work together. But getting there requires a fundamental shift in strategy.

The following security operations center best practices are the playbook for that transformation.

1. Build a Strong Foundation with the Right People and Processes

Stop hiring bodies and start building a team. Move from generalized security playbooks to methodical runbooks that combine your security analysts’ expertise with strategic automation and AI augmentation.

2. Prioritize Threat Detection and Response to Your Business Needs

It’s key to shift your team’s focus from managing alerts to actively hunting cyber threats. But with the sheer volume of today’s alerts pinging from sprawling stacks and an explosion of endpoints, the only way to free them up is by leveraging automation and AI to handle the majority of your Tier-1 alerts.

3. Automate the Mundane, Focus on the Critical

Automating repetitive and time-consuming tasks allows your limited resource of human expertise to be focused on more strategic activities, such as threat hunting and investigating complex and critical cases.

4. Embrace Continuous Improvement

The most overused wording in cybersecurity think pieces is probably “the constantly evolving threat landscape,” but the truth still stands. To keep up, SOCs must continuously improve their processes and technologies, which means regularly reviewing and updating security policies, tools, processes, and procedures, tracking and reporting KPIs, and being able to slice and dice case data to pinpoint problem areas.

5. Measure Everything

If you can’t measure it, you can’t fix it. Mean time to investigate, respond, and remediate aren’t vanity metrics — they are the vital signs of a SOC. When you can show your CISO that Hyperautomation slashed MTTI from hours to minutes (like this top 30 U.S. bank did), you’re no longer talking about a cost center; you’re talking about tangible, provable ROI.

6. Be Strategic About AI

AI is the biggest buzzword in security right now, with every vendor promising it can solve all of your problems. But it’s not a magic wand — and there’s a whole lot of AI-washed marketing out there right now. The real power of AI in the SOC is leveraging it to automate away the noise and grunt work and accelerate incident response, so your human SOC analysts can hunt cyber threats and handle complex incidents. And if an AI solution can’t prove its logic with evidence, it’s a black box that will kill trust and has no place in your SOC. See how to deploy AI in the SOC the right way.

7. Consolidate and Optimize

True optimization isn’t a “lift and shift” of your old, inefficient workflows to a new platform — it’s about fundamentally transforming your processes. Torq helps customers escape the tech debt of legacy SOAR by replacing dozens of brittle, code-heavy workflows with a handful of powerful and efficient automations built easily in Torq.

When migrating off a SOAR, Torq customers consistently consolidate their processes, achieving the same outcomes with significantly fewer and more efficient automations, often slashing their workflow count by 30% or more. Get the SOAR migration guide.

The Best SOC Tools

You can’t win today’s fight with yesterday’s technology. What’s the core solution you need to build a modern, autonomous SOC?

Torq HyperSOC

HyperSOC™ is the AI-driven platform I wish I had years ago. Designed specifically to crush the biggest challenges SOCs face, HyperSOC uses powerful, no-code automation to become the connective tissue for your entire security stack, so your cases are managed out of a single interface, and agentic AI autonomously handles 90% of Tier-1 case work.

Here’s how HyperSOC incorporates critical SOC best practices, built in:

Automates alert triage: HyperSOC ingests the flood of alerts across your stack, using automation and AI to add context, dismiss false positives, and group related alerts into a single, actionable case. It cuts through the noise so your team only sees what truly matters.
Connects your security tools: Torq has hundreds of pre-built integrations to instantly connect your SIEM, endpoint detection and response (EDR), threat intelligence, ticketing, and communication platforms into seamless, automated workflows.
Uses no-code, low-code, and AI-generated workflows: With Torq, you don’t need a team of developers to build complex automations. Torq’s drag-and-drop and AI-generated workflow-building capabilities mean anyone can create automations to handle everything from phishing investigation to endpoint containment.
Supports human-in-the-loop actions: Any AI deployed in the SOC needs to be transparent to be trustworthy. Torq makes it easy to inject human decision points into any AI workflow. Torq’s AI SOC Analyst Socrates can automatically investigate and enrich a case, then present it to a security analyst in Slack or Teams for a final decision on a critical action.

The Foundation for Transformation: Why SOC Best Practices Matter

The days of running a SOC on manual processes and sheer willpower are over. The only way to win against fast, AI-powered adversaries is to fight back with smarter, faster automation. By following security operations center best practices like prioritizing automation, empowering your team with the right tools, and quantifying outcomes through metrics, you can transform your SOC into a strategic value center.

Torq HyperSOC was designed specifically to automate and orchestrate modern SOC operations at scale. Want to learn more about how HyperSOC can help your security operations center get a whole lot more done, a whole lot faster?

Get the SOC Efficiency Guide packed with insights from my years in the trenches as a SOC leader.

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FAQs

What are the main challenges faced by a SOC?

The big ones haven’t changed much, but they’ve gotten worse: alert fatigue from overwhelming volumes of low-fidelity alerts, tool sprawl creating “swivel chair syndrome” where analysts waste time jumping between disconnected UIs, talent shortages making it impossible to hire your way out of the problem, and scalability issues as cloud adoption explodes the attack surface faster than teams can keep up. Add ransomware operators moving at unprecedented speed, and you’ve got a recipe for burnout and missed threats.

How does automation benefit SOC operations?

Automation isn’t about replacing analysts — it’s about stopping the waste of human expertise on tasks machines can do faster and more consistently. The real benefits: dramatically faster response times (seconds vs. hours), elimination of human error in repetitive tasks, consistent execution of runbooks regardless of who’s on shift, and freed-up analyst capacity for threat hunting and complex investigations. The SOCs we see thriving are the ones where automation handles 90% of Tier-1 work so humans can focus on the 10% that actually requires judgment.

What tools are essential for SOC efficiency?

At minimum: a SIEM for log aggregation and correlation, EDR for endpoint visibility and response, threat intelligence for context, and a case management/ticketing system for tracking investigations. But here’s the thing — having the tools isn’t enough. The magic happens when they’re connected. That’s where a Hyperautomation platform like Torq comes in: it becomes the connective tissue that lets your SIEM, EDR, IAM, threat intel, and ticketing systems actually work together without analysts manually bridging the gaps.

How does Torq integrate into a SOC?

Torq sits at the center of your security stack, connecting to your existing tools via hundreds of pre-built integrations — SIEM, EDR, IAM, email security, cloud platforms, ticketing, collaboration tools, and more. It doesn’t replace your tools; it makes them work together. Alerts flow in from any source, get enriched automatically, and either get handled autonomously by AI or get routed to analysts with full context already attached. The implementation is fast (days to weeks, not months) because Torq’s no-code and AI-generated workflows don’t require a dev team to build and maintain.

How do I measure SOC performance?

The metrics that matter: Mean Time to Detect (MTTD), Mean Time to Investigate (MTTI), Mean Time to Respond (MTTR), and Mean Time to Remediate. Track alert volume vs. cases created (your noise-to-signal ratio), false positive rates by source, cases handled per analyst, and SLA compliance. But don’t just measure — act on it. If a particular alert source generates 90% false positives, fix the detection logic or auto-dismiss it. If MTTR is climbing, figure out where the bottleneck is. Metrics should drive continuous improvement, not just populate dashboards.

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

Get a Demo

Hyperautomation Security Automation 101 Use Cases

MTTD vs. MTTR: Definition, Differences, & Why They Matter

By Torq

July 15, 2025

6 Minute Read

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When a cyberattack occurs, every second counts. Metrics like Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) are critical benchmarks in cybersecurity, helping organizations evaluate the effectiveness of their Security Operations Centers (SOCs). But what’s the difference between MTTD vs MTTR, and why do they matter?

Understanding and improving these metrics through strategic investments in security automation can significantly elevate your security posture, minimize damage, and keep your organization safe from threats.

MTTD vs. MTTR in Cybersecurity

Mean Time to Detect and Mean Time to Respond are both fundamental KPIs in cybersecurity, but each measures something distinct.

MTTD (Mean Time to Detect) measures the average time it takes your team to identify that a security incident has occurred. This metric primarily evaluates your monitoring and detection capabilities. A lower MTTD indicates your security stack can quickly recognize anomalies and suspicious activity.
MTTR (Mean Time to Respond) (sometimes called Mean Time to Resolve) tracks the average time required to respond to and resolve an incident fully. Speed matters; a recent SANS survey found that 33% of teams take hours to respond to threats. That’s too long. A shorter MTTR reflects strong incident response procedures and an agile, responsive security team.

MTTR often involves people and a series of steps that are needed to fix the issue. While MTTD may measure how well an automated alert system performs, MTTR often measures both your systems and the people you depend on to jump into action after an incident.

Together, these metrics illustrate your SOC’s maturity and operational effectiveness. Optimizing MTTD and MTTR directly reduces risk and overall damage from cybersecurity incidents.

How Automation Improves MTTD and MTTR

Security automation plays a pivotal role in dramatically enhancing both MTTD and MTTR, empowering security teams to scale detection and response effectively by:

Improving detection: Automated systems like SIEM, EDR, and XDR can swiftly correlate vast data sets, instantly surfacing anomalous activities. Automation reduces reliance on manual log analysis, ensuring immediate, accurate threat identification.
Accelerating response: Automation streamlines and accelerates incident response workflows. Tasks like enrichment, analysis, and containment that typically consume significant analyst time become nearly instantaneous. Automation eliminates the manual “grunt work,” allowing analysts to focus solely on complex or high-risk situations.
Reducing human error: With agentic AI handling the automation, repetitive tasks become consistently executed according to predefined procedures, drastically reducing the potential for mistakes and inconsistencies in handling security incidents.
Seamless integration: Hyperautomation platforms integrate seamlessly with SIEM, EDR, and XDR tools, delivering rapid data exchange, correlation, and enriched context. This tight integration creates an end-to-end, automated security ecosystem.

In short, automation significantly shrinks the time between detecting a threat and mitigating its impact, providing an immediate, measurable boost to your SOC performance.

How to Measure MTTD & MTTR (with Formulas)

Quantifying your incident response effectiveness requires clear measurement methods. Here’s how you calculate each:

Below is some practical guidance for measuring MTTD and MTTR:

Consistent tracking: Record timestamps at every key incident stage (i.e., detection, acknowledgment, investigation, and resolution).
Aggregate metrics: Regularly aggregate these timings to spot trends or inefficiencies in your process.
Benchmarking: Establish baseline metrics to evaluate the impact of new tools, processes, or automation investments.

MTTD and MTTR don’t exist in isolation. They are part of a broader landscape of incident response metrics that security teams should be tracking, including:

MTBF (Mean Time Between Failures): MTBF measures the average time between system failures. It’s useful for evaluating the reliability of security systems and predicting when future incidents might occur. A higher MTBF indicates stable security operations.
MTTF (Mean Time to Failure): MTTF tracks the average lifespan of a security tool or system component before a failure occurs. It’s commonly used to assess product reliability and helps organizations schedule proactive maintenance or upgrades.
MTTA (Mean Time to Assignment): MTTA is the average time it takes for an incident to be assigned to a specific analyst or team member after detection. Lower MTTA reduces response latency and enables teams to tackle threats more efficiently.
MTTI (Mean Time to Investigate): MTTI represents the average time taken from initial detection until the investigation is completed. Faster MTTI means threats can be understood and contained sooner, limiting potential damage.
MTTx (Mean Time to “Anything”): MTTx is a flexible metric used at Torq to track the average time to complete any defined security operation or workflow. It helps SOC teams measure efficiency across custom actions, automations, or specific tasks unique to their security processes.

Understanding these related metrics provides deeper insight into your security operations and helps identify specific bottlenecks or areas for improvement.

Key Incident Response Metrics Explained

Illustration showing MTTD vs MTTR metrics comparison

The Hyperautomation Domino Effect in Incident Response

Improving MTTD and MTTR isn’t just about moving faster; it’s about removing the friction between each phase of the incident response lifecycle. Torq Hyperautomation connects the dots across the entire workflow — from detection to assignment, investigation to remediation — creating a seamless chain reaction of automation that compounds every efficiency. Here’s how that automation domino effect plays out in practice:

Faster detection (MTTD): Torq reduces noise by automatically filtering out low-priority alerts and surfacing real threats faster. This shrinks MTTD and ensures analysts aren’t wasting time chasing false positives.

Faster assignment (MTTA): Once a threat is detected, a case is immediately built and assigned to the right resource within Torq’s intelligent case management dashboard. Torq decides in real time whether Socrates — the AI SOC analyst that offloads 90%+ of Tier-1 cases — or a human should take the lead, dynamically reassigning ownership if the threat escalates. That means alerts don’t sit in limbo, waiting to be noticed.

Faster investigation (MTTI): By the time an analyst gets involved, much of the work is already done. Torq HyperSOC automatically enriches and correlates incident data, while AI agents generate case summaries and assign relevant case runbooks. This allows analysts to dive straight into meaningful analysis, not manual triage.

Faster response (MTTR): Response time is reduced by how quickly and efficiently action is taken. Analysts can trigger remediation with a single click or let Socrates respond autonomously in milliseconds. Whether isolating a device, disabling a user, or launching a complex remediation strategy, action happens at machine speed.

Each improvement compounds the next, like dominoes falling one after another. The faster a threat is detected and assigned to the appropriate resource, the faster those resources can be actioned. With Torq Hyperautomation, every second saved is multiplied across the incident lifecycle, delivering exponential gains in speed, accuracy, and scale.

Reduce Your MTTD and MTTR with Torq Hyperautomation

Effectively managing cybersecurity threats requires fast detection and even faster responses. Clearly differentiating MTTD vs. MTTR and understanding related metrics like MTBF, MTTF, MTTA, and MTTI enables SOC teams to target improvements strategically.

The Torq Hyperautomation™ platform offers a proven way to dramatically lower both MTTD and MTTR through real-time incident detection, streamlined automated workflows, and reduced analyst workload. Torq helps organizations minimize alert fatigue, decrease caseload per analyst, and improve overall compliance and efficiency.

Ready to drastically reduce your MTTx? Get practice advice from our Field CISO on how to make your SOC more efficient.

Get the Guide

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

Get a Demo

AI AI SOC Hyperautomation

How AI is Redefining SOC Architecture

By Bob Boyle

July 14, 2025

9 Minute Read

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See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster.

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If you’ve been in cybersecurity longer than five minutes, you know one thing: legacy SOC architecture isn’t just showing its age — it’s creaking under the weight of today’s threats.

Cybersecurity analyst Francis Odum nailed it when presenting at Torq’s SKO 2025: “Legacy SOAR assumed everything starts in the SIEM. Now, teams connect automation directly to EDR, email, and identity systems.”.

This antiquated SOC architecture model, where every alert and log file is funneled into a Security Information and Event Management (SIEM) solution for analysis, is too slow, too rigid, and creates too many bottlenecks to support today’s exploding security event and data pipeline. Modern SOCs need speed, scalability, and a level of intelligence that legacy architecture simply cannot provide. They need a new approach that is purpose-built for the AI era.

What is AI SOC Architecture?

AI SOC Architecture

AI SOC architecture is a modern, AI-augmented design for SOCs that decentralizes data processing, automates low-level tasks, and enables agentic systems to proactively investigate, triage, and respond to threats.

AI SOC architecture is not just about adding AI to the stack — it’s about re-architecting the stack around AI. The traditional SOC model relies on aggregating data into a centralized point of analysis before taking action. In contrast, the AI SOC places agentic, AI-powered Hyperautomation at the center of operations — integrating directly with data lakes, security tools, and workflows to create a unified, AI-native control plane. This architecture ensures a single source of AI truth, distributed evenly across the entire security stack.

Shifting the SOC Foundation

“Architecture is changing. Automation tools like Torq are being plugged directly into FDR and identity systems — not after the SIEM, but before it.”
Francis Odum, Software Analyst Cyber Research

For years, the SOC has been centered around the SIEM. Disparate security vendor solutions would feed hundreds of thousands of logs, events, and alerts into the SIEM for security analysts to manually parse through, correlate, and eventually return to the respective point solution(s) to begin the remediation process. This model created a lot of friction, leading to several chronic problems, including:

Process debt: This process would cause what we in the biz call “swivel chair syndrome,” as it often isn’t as simple as a single straight line from detection to SIEM to remediation. Instead, the lengthy investigation had analysts swiveling back and forth between the SIEM and security tools several times before reaching a conclusion hours later.
Central bottlenecks: While a centralized approach to security event management once seemed favorable, SIEM solutions were not designed for the volume of data produced by the multi-cloud environments that organizations have built — let alone the deployment of AI to help alleviate the manual filtering of that data. This creates a massive data bottleneck and, worse, a single point of failure for the SOC to rely upon.
Reactive, delayed response: In addition to scalability concerns, this is also a largely reactive approach, requiring analysts to use the SIEM to begin the manual investigation process long after an incident occurs. This slows down critical SOC reporting metrics like Mean-Time-To-Detection (MTTD) and Mean-Time-To-Response (MTTR). Legacy SOAR solutions attempted to solve this problem but did not promise faster orchestration or response times due to limited and inflexible automation playbooks.

Between sifting through an overwhelming amount of logs in a centralized SIEM solution and battling the manual efforts of legacy SOAR automation, security analysts find themselves drowning in disconnected alerts and burning out at an alarming rate.

An AI SOC architecture flips this on its head, shifting the SIEM further left in the security event lifecycle, particularly as many organizations continue to adopt a multi-SIEM strategy to offset increasing storage costs from legacy SIEM vendors.

Gartner’s recent Reference Architecture Brief: SIEM-Centric Security Operations report points out that as the industry largely shifts away from legacy SOAR solutions, it is seeing more advanced capabilities come from platforms centered around AI SOC Analysts, which produce stronger outcomes for analyst augmentation and security automation.

What Does AI-Native SOC Architecture Look Like?

In the same report, Gartner breaks down the Security Operations Center architecture into two distinct components: Security Operations Tools (e.g., SIEM and Detection-as-Code solutions) and SOC Actions (e.g., manual triage, investigation, threat hunting, and response via the SOC Team). Gartner calls out SecOps Workflow Automation, which consists of third-party automation and AI SOC analysts, bridging the gap between these two pillars of the SOC.

This is the heart of the AI-native SOC Architecture — a foundation of agentic AI and Hyperautomation built for the modern cloud-first SOC environment and designed for simplicity, extensibility, and scale.

Agentic AI

Agentic AI sits at the core of the AI SOC architecture. Rather than burdening human analysts with manually piecing together thousands of logs and events, an AI-native SOC leverages a multi-agent system (MAS) to handle up to 90% of Tier-1 security analysts’ tasks. These specialized AI agents have a deep understanding of the SOC environment, allowing them to plan incident response, make complex decisions, and take remediation actions autonomously.

Hyperautomation

Hyperautomation is the engine that drives autonomous response and the glue that connects agentic AI with the rest of the SOC solutions to bridge the gap between Security Operations Tools and SOC actions. With limitless no-code or AI-generated integrations, the Hyperautomation engine is the delivery system allowing agentic AI to take action, automating anything from simple alert triage to complex, multi-step incident responses.

Enterprise-Grade Security Architecture

Unlike monolithic legacy SIEM and SOAR solutions, an AI-native SOC architecture is built for cloud-first scalability and flexibility. Underpinned by an extensible security architecture, horizontal and elastic scalability allows the SOC to dynamically process and prioritize hundreds of thousands of events from various data sources, ensuring the most critical information is surfaced without interruption.

Torq’s AI SOC Architecture

Torq is built for this moment. It’s not about retrofitting AI into a legacy architecture — Torq is an enterprise-ready, AI-native platform purpose-built from the ground up to solve existential SOC challenges like alert fatigue, tech sprawl, and analyst burnout.

Torq’s AI SOC architecture begins with the ability to integrate with any solution across the entire security stack and beyond — whether it’s EDR, IAM, email phishing, threat intelligence, collaboration and communication tools, and more.

This direct integration enables agentic AI to not only take autonomous remediation actions across Tier-1 and Tier-2 security use cases but also allows AI agents to retrieve and enrich data directly from the source, regardless of what data may be missing (or difficult to find manually) from SIEM logs. As the modern SOC scales to produce tens of thousands of alerts per day, Torq’s AI-SOC architecture can seamlessly handle massive alert volumes without creating single-point bottlenecks.

HyperSOC™

Torq HyperSOC, the AI-powered autonomous SOC solution, was also explicitly designed to support AI deployment across the modern SOC. While legacy SOAR solutions have bolted-on workarounds to handle case management once an analyst has manually pulled the relevant data from a SIEM tool, Torq HyperSOC is comprised of intelligent case management and Socrates, the agentic AI SOC Analyst, embedded directly in each security case. Socrates summarizes key findings, suggests next steps, and analyzes case runbooks for autonomous remediation.

The Multi-Agent System

Socrates coordinates Torq’s multi-agent system, a team of AI Agents that can autonomously handle the vast majority of Tier-1 and Tier-2 use cases, reduce human analysts’ workload by over 95% from initial investigation to final remediation, and enable SOC teams to tackle up to 5x more security cases in a single day without adding headcount.

Socrates leads Torq’s multi-agent AI system, autonomously resolving cases, reducing analyst workload by 95%, and enabling SOC teams to handle 5x more incidents daily.

Model Context Protocol

To help Torq’s system of AI agents communicate reliably across a limitless amount of integrated security tools and other AI solutions deployed in the SOC, Torq’s AI SOC architecture also natively supports Model Context Protocol (MCP), an open protocol designed to standardize how applications provide context to AI Agents to retrieve contextual information from applications and systems.

Human-on-the-Loop AI Guardrails

Finally, this entire AI architecture is designed with the appropriate AI guardrails that provide the explainability, audibility, and control organizations require. These guardrails ensure there is always a human on the loop to avoid AI hallucinations and so SOC teams remain in control of critical decisions.

AI SOC Architecture in Action: Phishing Response

Here’s how AI SOC architecture changes the game for a common use case: phishing.

A phishing email lands in an employee’s inbox. In a legacy SOC, the detection fires into the SIEM, where it joins a queue of thousands of other alerts. An analyst eventually triages it, pivots to the email security tool to pull headers, checks threat intel for the sender domain, moves to EDR to scan the endpoint, switches to IAM to reset credentials, opens a ticket, documents everything, and notifies the user. Best case: 45 minutes. Realistic case: hours — if it doesn’t get lost in the noise entirely.

The SIEM bottleneck isn’t just slow; it’s a single point of failure that forces analysts into “swivel chair syndrome,” bouncing between tools while threats dwell.

With AI SOC architecture, automation connects directly to email security, EDR, and IAM — not after the SIEM, but alongside it. When the phishing email is detected, Torq’s agentic AI immediately:

Quarantines the email and extracts indicators of compromise
Enriches the alert with threat intelligence directly from the source
Scans the recipient’s endpoint for malicious payloads
Resets the user’s credentials and enforces step-up authentication
Creates a case with full context, AI-generated summary, and audit trail
Notifies the user with next steps

Organizations using Torq’s AI SOC architecture have reduced phishing response times from hours to under 60 seconds — a 95%+ improvement in MTTR. Analysts aren’t stuck on Tier-1 triage; they’re freed to focus on complex investigations that actually require human judgment.

From AI-Enabled to AI-Architected

Legacy SOC architecture isn’t just outdated — it’s actively holding organizations back. True AI-native SOC architecture, like Torq HyperSOC, breaks through these barriers. It offers immediate, measurable outcomes, dramatically improving analyst effectiveness, reducing costs, and transforming security postures from reactive to proactive.

In Francis Odum’s words: “The market is ready for next-gen, AI-powered solutions. These aren’t future-state ideas; they’re delivering real-world results right now.”

The future of cybersecurity isn’t just AI-enabled; it’s AI-architected.

Get the AI or Die Manifesto to learn strategic considerations and evaluation criteria for deploying AI in the SOC from the ground up.

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FAQs

What is AI SOC architecture?

AI SOC architecture is a modern design for security operations that places agentic AI and hyperautomation at the center of the SOC — not bolted on as an afterthought. Unlike traditional architectures that funnel everything through a centralized SIEM before taking action, AI SOC architecture integrates directly with security tools (EDR, IAM, email, cloud) to enable faster detection, autonomous triage, and real-time response.

How does AI SOC architecture enhance security operations?

AI SOC architecture eliminates the bottlenecks and manual handoffs that slow down traditional SOCs. By deploying agentic AI that can autonomously investigate, enrich, and remediate threats, organizations see dramatic improvements in key metrics: faster mean time to detect (MTTD), faster mean time to respond (MTTR), and up to 95% reduction in Tier-1 analyst workload. Security teams handle more cases without adding headcount, and analysts focus on high-value work instead of repetitive triage.

Why is Hyperautomation important in AI SOC architecture?

Hyperautomation is the engine that connects agentic AI to the rest of the security stack. Without it, AI is just another tool that generates recommendations that analysts still have to act on manually. Hyperautomation enables AI agents to actually take action — quarantining endpoints, revoking access, blocking IPs, creating cases — across hundreds of integrated tools.

What are the challenges of implementing AI SOC architecture?

The biggest challenges are organizational, not technical. Teams accustomed to legacy SIEM-centric workflows need to shift their mindset from reactive, centralized analysis to proactive, distributed automation. Integration sprawl can also be a concern — AI SOC architecture requires connecting to tools across the entire stack, which is why platforms like Torq offer limitless no-code integrations. Finally, governance matters: AI guardrails, explainability, and human-on-the-loop controls are essential to maintain trust and compliance.

How does AI SOC architecture integrate with existing systems?

Platforms like Torq integrate directly with SIEMs, EDRs, IAM solutions, email security, cloud platforms, ticketing systems, and collaboration tools via APIs, webhooks, and native connectors. The key difference is that automation no longer waits for data to flow through the SIEM first; it connects directly to sources for faster enrichment and response while still feeding relevant data back to the SIEM for logging and compliance.

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

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AI Security Engineering Use Cases

Take Control with Torq’s AI Data Transformation

By Torq

July 11, 2025

9 Minute Read

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In today’s enterprise environment, raw data flows in from countless sources — often messy, fragmented, and incompatible. Effective data transformation is essential for turning this fragmented data into actionable, compliant, and secure intelligence.

With Torq’s AI Data Transformation, organizations can achieve seamless, scalable data workflows without writing code, dramatically enhancing security operations and compliance.

The Role of Data Transformation in Cybersecurity

What is Data Transformation?

Data transformation is the process of converting, cleaning, and manipulating raw data into a structured format that is suitable for analysis or other data processing tasks.

Data transformation is critical for:

Data quality: Removing inconsistencies, duplicates, and errors.
Data compatibility: Ensuring different systems and workflows can use the same data formats.
Data reliability: Maintaining trust in analytics, compliance reporting, and operational decisions.

In a security context, data transformation keeps Hyperautomated workflows running smoothly by ensuring every downstream step receives data in the right format, at the right time. Without it, automation breaks, alerts go unprocessed, and compliance gaps widen.

How Data Transformation Works

Data discovery: Identify and profile raw data sources to understand structure, quality, and required transformations.
Data mapping: Define how fields will be transformed, matched, filtered, joined, and aggregated for the target system.
Data extraction: Move data from source systems (structured or unstructured) to a staging or target environment.
Code generation & execution: Use SQL, Python, or transformation tools to convert raw data into analytics-ready formats, running on a set schedule.
Review: Validate transformation accuracy, completeness, and alignment with business requirements.
Sending: Deliver transformed, structured data to its final destination, such as a data warehouse or analytics platform.

ETL and ELT in Data Transformation

In data engineering, ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are proven methodologies for shaping and preparing information. ETL transforms data before loading it into a data warehouse, while ELT loads raw data first and performs transformation inside the warehouse. Both approaches are designed to ensure clean, structured, and trustworthy data for analytics, reporting, and compliance.

Types of Data Transformation

The main types of data transformation used in security automation include:

Aggregation: Summarizing multiple data points (e.g., calculating the average CVSS score).
Anonymization: Obfuscating personal information to protect sensitive data, essential for compliance with regulations like GDPR and HIPAA.
Filtering: Selecting only the most relevant records (e.g., isolating high-severity vulnerabilities).
Flattening: Converting nested or hierarchical data (such as JSON) into a flat, single-level table format so fields are directly accessible for querying, filtering, aggregation, and joining without complex parsing.
Conditional Logic: Applying predefined rules to determine which data proceeds through the workflow.
Data Cleansing: Removing invalid, duplicate, or incomplete data to improve accuracy.
Data Enrichment: Enhancing records with intelligence from external threat feeds or authoritative databases.

Whether you’re extracting key attributes from JSON logs or merging disparate datasets, these transformation types ensure raw data becomes structured and usable intelligence.

How AI Data Transformation Accelerates Security and Compliance

AI data transformation automates complex processes such as converting formats, improving data integrity, and enhancing data observability. AI significantly speeds up compliance reporting, streamlines incident response, and provides richer, actionable data for security analytics.

Torq’s AI Data Transformation translates natural language into precise data commands, making these sophisticated tasks accessible to all users. Torq’s AI Data Transformation brings automation and intelligence to the process along with:

Customizability: Edit or rewrite any command to suit your needs.
Testability and reproducibility: Test transformations and validate results for precise control.
Flexibility: Easily tweak transformations without disrupting your workflow.
Visibility: See prompts, code, and results at every step — zero guesswork.

While other solutions leave you in the dark, using monolithic parsing that makes it challenging to edit or troubleshoot, Torq keeps you in control through micro-transformations. Every transformation in Torq is testable, customizable, and modifiable with just a click, ensuring your automation runs precisely as intended.

For security teams, this means faster threat enrichment, streamlined compliance reporting, and better data lineage tracking — all with built-in data privacy compliance.

Getting Started with Torq’s AI Data Transformation Operator

The Torq AI Data Transformation Operator is a workflow step that lets you manipulate JSON data inside Torq without needing deep programming skills. It combines AI-powered natural language prompts with deterministic JSON processing using JQ, a high-performance JSON transformation language. AI helps you write transformations in plain language, then Torq converts them into JQ commands that execute consistently.

How It Works

Input your data: Pass JSON from a previous workflow step or paste it directly into the operator.
Describe your transformation in plain language. For example:
- “Extract email, department, and action from each entry.”
- “Remove results where department is equal to Engineering.”
- “Group by department and count actions.”
AI converts your prompt to JQ: The operator generates JQ code from your instructions. The AI step ends here; the deterministic JQ engine handles the actual execution.
Chain multiple instructions: You can stack transformations — extraction, filtering, aggregation, string manipulation — all in one operator, with each step feeding into the next.
Preview and adjust: See the output for each step before finalizing, and tweak the natural language instructions or the generated JQ directly.
Save and reuse: If you create a transformation you’ll need often, you can save it as a custom step and reuse it across workflows or even share it across workspaces.

What You Can Do With It

The Data Transformation Operator supports a wide range of operations:

Mapping and extraction (pull only the fields you care about)
Renaming keys
Converting data types
Filtering and sorting
Conditional logic (if/else rules)
Math functions (averages, sums, etc.)
String manipulation (splitting, regex)
Restructuring JSON formats

Example Prompts

Need ideas? Here are a few natural language prompts and the associated JQ commands the Data Transformation operator could generate.

Natural Language Prompt	AI Translated JQ Command	Security Impact
“Extract all high severity vulnerabilities”	.vulnerabilities[] \| select(.severity == “high”)	Quickly prioritize critical security threats
“Group alerts by source IP”	group_by(.source_ip)	Identify potential attack patterns or compromised assets
“Calculate the average CVSS score”	[.[].cvss_score] \| add / length	Assess the overall vulnerability landscape

In security workflows, raw alerts and logs often come in messy, verbose JSON. The AI Data Transformation Operator lets you clean, normalize, and reformat that data on the fly, so the next steps in your workflow — whether enrichment, correlation, or reporting — get exactly the data they need in the right shape.

Torq Use Cases: Real-World AI Data Transformation in Security Operations

1. Normalizing SIEM Alerts Before AI Analysis

Challenge: SIEM alerts arrive in varied JSON formats depending on the source (cloud, endpoint, identity). Some include deeply nested keys or inconsistent field names.

Transformation:

Extract only relevant fields (timestamp, src_ip, dst_ip, event_type, username).
Rename fields for consistency (dst_ip → Destination IP).
Convert timestamps into ISO 8601 for uniformity.

Outcome: Socrates, the AI SOC Analyst, receives a clean, uniform alert format for faster, more accurate triage.

2. Filtering Out Benign Events in EDR Logs

Challenge: EDR telemetry is high-volume, and not every event is actionable (e.g., routine system updates).

Transformation:

Filter out entries where process_name equals known benign processes (e.g., svchost.exe in a non-suspicious path).
Keep only events matching defined high-risk criteria (e.g., unsigned binaries, rare parent processes).

Outcome: Reduces noise before enrichment, allowing workflows to trigger only on meaningful events.

Challenge: IAM tools generate individual failed login events, making it hard to see patterns.

Transformation:

Group events by username and source_ip.
Count the number of failed attempts per user per IP within a set timeframe.
Output only users exceeding a defined threshold.

Outcome: Aggregated insight triggers an automated account lockout or SOC escalation.

4. Enriching IOC Data Before Threat Hunting

Challenge: Incoming threat intelligence feeds may contain minimal metadata on indicators.

Transformation:

Attach GeoIP data for IP addresses.
Add WHOIS registration details for domains.
Convert lists into an array of {indicator_type, value, source, risk_score} objects.

Outcome: Analysts and automation workflows have full context without additional lookups.

6. Preparing Audit Logs for Compliance Reporting

Challenge: Audit logs contain extra data that auditors don’t need, making reports bulky.

Transformation:

Remove debug and low-value keys.
Sort events chronologically.
Output as a simplified JSON or CSV format matching compliance templates.

Outcome: Audit-ready reports generated instantly without manual editing.

These examples show how Torq’s AI Data Transformation Operator turns messy and inconsistent security data into clean, actionable intelligence that feeds directly into AI analysis, automation workflows, and case management.

Choosing the Right Data Transformation Tools and Software

Selecting the right data transformation software is critical for ensuring your workflows remain efficient, compliant, and adaptable as your organization’s needs evolve. When evaluating options, consider the following criteria:

Ease of use and no-code or AI-driven functionality: Look for platforms offering intuitive interfaces and visual or AI-generated workflow builders so technical and non-technical users can wrangle complex data without writing scripts. This reduces engineering bottlenecks and speeds up deployment.
Integration capabilities: Your data transformation tool should connect seamlessly with your existing security stack (SIEM, SOAR, EDR, threat intelligence feeds) and compliance systems (GRC, audit platforms). Native connectors and API support ensure smooth data integration across multiple environments.
Scalability: As data volumes grow, especially in large enterprise and SOC environments, the platform must handle high-throughput processing without latency issues. Real-time or near-real-time transformation capabilities are essential for automation-driven incident response.
Customizability and flexibility: Every organization has unique data mapping, aggregation, and enrichment needs. A robust platform allows you to tailor transformation logic, apply conditional rules, and reuse transformation templates without disrupting other workflows.
Data governance and compliance support: Choose a solution that offers data lineage tracking, audit logs, and privacy controls to meet data privacy compliance regulations like GDPR, CCPA, and industry-specific standards.

Why Torq Stands Out

Torq’s AI Data Transformation capabilities meet — and exceed — these criteria:

No-code AI workflows: Transform complex JSON or other structured data using plain-language prompts automatically converted into precise JQ commands.
Extensive integrations: 1,000+ prebuilt connectors for security, IT, and compliance tools.
Enterprise-scale performance: Designed to handle large-scale, real-time data transformations without performance degradation.
Full visibility and governance: Every transformation is testable, traceable, and compliant with your data governance policies.

Embrace AI-Driven Data Transformation

In a world where data flows faster and threats evolve by the minute, transforming raw, fragmented information into trusted, actionable intelligence is a competitive advantage. Torq’s AI Data Transformation delivers that capability, combining speed, compliance, and control in a no-code platform that works at enterprise scale. From unifying multi-source security alerts to streamlining compliance reporting, Torq ensures your workflows are reliable, transparent, and ready for whatever comes next.

See the difference for yourself. Request a personalized demo of Torq’s AI Data Transformation today and start turning your data into a decisive asset.

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FAQs

What is data transformation vs. AI data transformation?

Data transformation is the process of converting raw data from one format or structure into another to make it clean, consistent, and usable for analysis, storage, or automation. It typically involves tasks like data cleansing, mapping, aggregation, and enrichment.

AI data transformation uses artificial intelligence — often with natural language processing (NLP) — to automate these steps. Instead of manually writing scripts or queries, users can describe the desired transformation in plain language, and the AI generates the logic, executes it, and allows for easy customization. This speeds up the process, reduces technical barriers, and maintains accuracy and compliance.

What is a data warehouse vs. data lake?

A data warehouse stores structured, processed data in a consistent format, optimized for fast querying, analytics, and compliance reporting.

A data lake stores raw, unprocessed data — including structured, semi-structured, and unstructured formats — for flexible exploration, large-scale storage, and future processing.

Organizations often use both: the data lake for cost-effective retention of all data, and the data warehouse for ready-to-use insights that power day-to-day decision-making.

Why is data transformation important?

Data transformation is essential because it:

Improves data quality by removing errors, duplicates, and inconsistencies.
Ensures compatibility between different tools, systems, and formats.
Supports compliance by enabling privacy controls, audit trails, and data lineage tracking.
Enables better decisions by ensuring analytics, automation, and reporting run on reliable, well-structured data.
Speeds up workflows by making data ready for automation and integration without manual intervention.

In security operations, data transformation ensures that alerts, logs, and intelligence feeds can flow seamlessly into detection, investigation, and response workflows.

What is the difference between ELT and ETL?

ETL (Extract, Transform, Load): Data is extracted from sources, transformed into the desired format, and then loaded into a data warehouse or destination system. This is ideal when you need consistent, cleaned data before it’s stored.

ELT (Extract, Load, Transform): Data is extracted and loaded into the warehouse first, then transformed inside that environment. This approach is useful when storage is cheap and you want flexibility to transform data on demand.

Both approaches have their place, and modern AI data transformation tools like Torq can operate effectively in either ETL or ELT pipelines.

What are examples of data transformation?

Common examples include:

Format conversion: Converting XML to JSON.
Data mapping: Aligning “src_ip” and “source_address” fields into a unified “source_ip” field.
Filtering: Selecting only high-severity vulnerabilities from a dataset.
Aggregation: Grouping alerts by source IP or calculating average CVSS scores.
Enrichment: Adding threat intelligence data (e.g., IP reputation) to security alerts.
Data cleansing: Removing duplicate log entries or fixing malformed timestamps

Ready to automate everything?

“Torq takes the vision that’s in your head and actually puts it on paper and into practice.”

Corey Kaemming, Senior Director of InfoSec

“Torq HyperSOC offers unprecedented protection and drives extraordinary efficiency for RSM and our customers.”

Todd Willoughby, Director

“Torq saves hundreds of hours a month on analysis. Alert fatigue is a thing of the past.”

Phillip Tarrant, SOC Technical Manager

“The only limit Torq has is people’s imaginations.”

Gai Hanochi, VP Business Technologies

“Torq Agentic AI now handles 100% of Carvana’s Tier-1 security alerts.”

Dina Mathers, CISO

“Torq has transformed efficiency for all five of my security teams and enabled them to focus on much more high-value strategic work.”

Yossi Yeshua, CISO

Get a Demo

Contents

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Where Legacy SOAR Breaks for MSSPs

Hyperautomation: Built for MSSP Scale

How MSSPs Use Torq Hyperautomation

The MSSP Hyperautomation Playbook: How HWG Sababa Doubled SOC Output

Join the World’s Top MSSPs in Ditching Legacy SOAR

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The 5 Hidden Costs of SOAR for MSSPs — And What to Do Instead

The MSSP Hyperautomation Playbook: How HWG Sababa Doubled SOC Output

4 MSSP Trends: Differentiate Your Business with CTEM, AI SOC, and More

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Contents

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The Top 4 MSSP SOCs Challenges

Hyperautomation: The Solution to MSSP SOC Challenges

HWG Sababa: SOC Automation Results in Just Weeks

Automating 55% of Monthly Alerts

Productivity and Operational Capacity Nearly Doubled

Enhanced Analyst Morale and Retention

Reduced Customer-Side Effort

Strategic Adoption Across the Organization

Hyperautomation: A Clear MSSP SOC Differentiator

Looking Forward: A Hyperautomation-First Mindset

Ready to Scale Your MSSP SOC?

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What Makes Torq AMP Different

Why Join AMP?

AMP in Action

Google Cloud + Torq: Powering Cloud-Scale Hyperautomation

Wiz + Torq: Accelerating Cloud Risk Response

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Contents

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The Evolution from SDLC to SSDLC

The Importance of Integrating SSDLC into Modern Development

Where Legacy SOAR Fails: Lack of SSDLC Integration

How Torq Hyperautomation Integrates SSDLC by Design

Built-in SSDLC Framework

Automated Testing and Continuous Validation

Environment Segmentation: Development, Staging, and Production

Agile Workflow Development with Enhanced Security

Hyperautomation is Essential for SSDLC

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Contents

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Why Legacy SOAR Breaks MSSP Economics

What Replaces SOAR: Hyperautomation for MSSPs

Hidden Cost #1: SLA Exposure and Penalties

Hidden Cost #2: Legacy Security Environments

Hidden Cost #3: Integration and Maintenance Tax

Hidden Cost #4: Alert Volume and Manual Triage

Hidden Cost #5: Continuous Optimization and Reporting

The Bottom Line for MSSPs

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