Autonomous SOC ROI | Security Outcomes and Metrics

Pillar

Autonomous SOC — From Playbooks to Decision Systems

Find out why.

Pillar

Autonomous SOC — From Playbooks to Decision Systems

Find out why.

Autonomous SOC — From Playbooks to Decision Systems

Autonomous Security

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Autonomous Security

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Security outcomes

Autonomous security: production data from Autonomous SOCs

Autonomous security: production data from Autonomous SOCs

Automation speeds up work. It does not remove the decision burden. Autonomous security does.

Automation speeds up work. It does not remove the decision burden. Autonomous security does.

Learn more

Learn more

Learn more

These aren't isolated improvements

They're structural effects of a different execution model.

MTTR

20 secs

instead of 6 minutes

Analyst hours removed

~150 hrs

per day from investigation and triage

Autonomous actions

~90%

executed without human intervention

Operating cost

~$100K

annually instead of $800K–$1M

Why this matters

Why this matters

Why this matters

CISOs

Risk posture becomes predictable. Response speed stops depending on shift schedules and approval chains.

CISOs

Risk posture becomes predictable. Response speed stops depending on shift schedules and approval chains.

CISOs

Risk posture becomes predictable. Response speed stops depending on shift schedules and approval chains.

CFOs

Security costs flatten. Volume no longer drives headcount.

CFOs

Security costs flatten. Volume no longer drives headcount.

CFOs

Security costs flatten. Volume no longer drives headcount.

SOC Directors

Your team handles strategy. The system handles volume. Analyst burnout drops.

SOC Directors

Your team handles strategy. The system handles volume. Analyst burnout drops.

SOC Directors

Your team handles strategy. The system handles volume. Analyst burnout drops.

The four outcomes of switching to Sirp

The four outcomes of switching to Sirp

Response speed becomes structural

New product

To be clear: 6-minute MTTR is excellent. These were mature SOCs with optimized workflows. The 18× improvement came from removing the execution queue entirely.

With Sirp, decision and execution happen in the same step. Containment windows for ransomware and lateral movement are measured in minutes. When your MTTR is 20 seconds, you're inside the window.

Response speed becomes structural

Volume stops scaling with headcount

Analyst work changes completely

The cost curve flattens

Response speed becomes structural

New product

To be clear: 6-minute MTTR is excellent. These were mature SOCs with optimized workflows. The 18× improvement came from removing the execution queue entirely.

With Sirp, decision and execution happen in the same step. Containment windows for ransomware and lateral movement are measured in minutes. When your MTTR is 20 seconds, you're inside the window.

Response speed becomes structural

Volume stops scaling with headcount

Analyst work changes completely

The cost curve flattens

Response speed becomes structural

New product

To be clear: 6-minute MTTR is excellent. These were mature SOCs with optimized workflows. The 18× improvement came from removing the execution queue entirely.

With Sirp, decision and execution happen in the same step. Containment windows for ransomware and lateral movement are measured in minutes. When your MTTR is 20 seconds, you're inside the window.

Response speed becomes structural

Volume stops scaling with headcount

Analyst work changes completely

The cost curve flattens

New product

New product

Real deployments

+

Global Fintech SOC

120K alerts/day

4 regions

Highly regulated

Before Sirp

11 analysts, approval gates, 4–6 hour case age

After Sirp

2 analysts (oversight), <30 second case age, <5% human review

Results

7× cost reduction, zero audit findings, more thorough compliance documentation

The unexpected

Audit trail improved. Automated logging is more complete than manual documentation.

+

SaaS Infrastructure Company

Cloud-native

High analyst turnover

Alert fatigue

Before Sirp

Tiered L1→L2→L3 escalation model

After Sirp

System-first resolution, single oversight team

Results

92% autonomous actions, zero routine escalations, team stayed intact

The moment

“We ran parallel for 30 days. The autonomous system caught 3 incidents the human team missed due to the queue backlog. That ended the debate.”

Real results

Real deployments

+

Global Fintech SOC

120K alerts/day

4 regions

Highly regulated

Before Sirp

11 analysts, approval gates, 4–6 hour case age

After Sirp

2 analysts (oversight), <30 second case age, <5% human review

Results

7× cost reduction, zero audit findings, more thorough compliance documentation

The unexpected

Audit trail improved. Automated logging is more complete than manual documentation.

+

SaaS Infrastructure Company

Cloud-native

High analyst turnover

Alert fatigue

Before Sirp

Tiered L1→L2→L3 escalation model

After Sirp

System-first resolution, single oversight team

Results

92% autonomous actions, zero routine escalations, team stayed intact

The unexpected

“We ran parallel for 30 days. The autonomous system caught 3 incidents the human team missed due to the queue backlog. That ended the debate.”

Why these metrics move together

This isn't five separate improvements. It's one architectural change.

Traditional SOC

Decisions happen in meetings and tickets. Execution waits for humans. Speed is limited by availability. Cost scales with volume.

Traditional SOC

Decisions happen in meetings and tickets. Execution waits for humans. Speed is limited by availability. Cost scales with volume.

Traditional SOC

Decisions happen in meetings and tickets. Execution waits for humans. Speed is limited by availability. Cost scales with volume.

Autonomous SOC

Decisions happen in-system. Execution happens at decision time. Speed is limited by compute. Cost is decoupled from volume.

Autonomous SOC

Decisions happen in-system. Execution happens at decision time. Speed is limited by compute. Cost is decoupled from volume.

Autonomous SOC

Decisions happen in-system. Execution happens at decision time. Speed is limited by compute. Cost is decoupled from volume.

The key difference: decision placement

Workflow automation makes humans faster. Autonomous execution removes humans from the execution path entirely. That's why the outcomes cascade.

The key difference: decision placement

Workflow automation makes humans faster. Autonomous execution removes humans from the execution path entirely. That's why the outcomes cascade.

The key difference: decision placement

Workflow automation makes humans faster. Autonomous execution removes humans from the execution path entirely. That's why the outcomes cascade.

What the system doesn't handle

The system escalates when:

Confidence falls below policy threshold

Attack pattern is novel or outside training data

Context requires business knowledge

Multiple conflicting signals with ambiguous risk

Escalation rate: 5–10% of investigations

False positive rate: <2%

Humans handle ambiguity and strategy. The system handles volume and routine execution.

How we measured this:

3 enterprise SOCs

Fintech, SaaS, and healthcare.

3 enterprise SOCs

Fintech, SaaS, and healthcare.

3 enterprise SOCs

Fintech, SaaS, and healthcare.

90-day window

90-day window post-stabilization (excludes tuning and pilots).

90-day window

90-day window post-stabilization (excludes tuning and pilots).

90-day window

90-day window post-stabilization (excludes tuning and pilots).

Millions of alerts

Millions of alerts across EDR, cloud, identity, SaaS, endpoint.

Millions of alerts

Millions of alerts across EDR, cloud, identity, SaaS, endpoint.

Millions of alerts

Millions of alerts across EDR, cloud, identity, SaaS, endpoint.

Full chain measured

Detection → triage → decision → containment

Full chain measured

Detection → triage → decision → containment

Full chain measured

Detection → triage → decision → containment

Excluded: Test incidents, training data, simulations, deployment phase, cases requiring human judgment

What this means for your SOC

If your SOC depends on human availability, tickets, and shift coverage, your performance is capped by how fast analysts work and how many you can hire.

When decisions are policy-bound and system-executed, response speed becomes predictable, cost becomes flat, quality becomes consistent, and scale becomes an infrastructure question.

The operating model changes. The outcomes follow.

Autonomous security isn't theoretical.

Autonomous security isn't theoretical.

The question isn't whether autonomous SOCs work.  The question is whether your current model can keep up.

The question isn't whether autonomous SOCs work.  The question is whether your current model can keep up.

Get a demo

Get a demo

Get a demo

Self-driving SOC — governed, AI-native security operations.
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Autonomous Security

United States

7735 Old Georgetown Rd, Suite 510

Bethesda, MD 20814

+1 888 701 9252

United Kingdom

167-169 Great Portland Street,

5th Floor, London, W1W 5PF

© 2026 SIRP Labs Inc. All Rights Reserved.

Self-driving SOC — governed, AI-native security operations.
Powered by OmniSense™

Autonomous Security

United States

7735 Old Georgetown Rd, Suite 510

Bethesda, MD 20814

+1 888 701 9252

United Kingdom

167-169 Great Portland Street,

5th Floor, London, W1W 5PF

© 2026 SIRP Labs Inc. All Rights Reserved.

Self-driving SOC — governed, AI-native security operations.
Powered by OmniSense™

Autonomous Security

United States

7735 Old Georgetown Rd,
Suite 510, Bethesda, MD 20814

+1 888 701 9252

United Kingdom

167-169 Great Portland Street,
5th Floor, London, W1W 5PF

© 2026 SIRP Labs Inc. All Rights Reserved.