AI SOC
A security operations center that runs at machine speed
Five coordinated AI agents handle detection, triage, investigation, containment, and reporting. Analysts receive pre-triaged cases with evidence and recommended actions — not raw alert queues.
95%
reduction in analyst time per alert
<60s
mean time to detect
24/7
autonomous coverage, no night shift
How the AI SOC works
Detection that never sleeps
ManySignal's Detect agent runs behavioral rules and anomaly models continuously against your telemetry. Every finding is staged with context — asset, entity history, related events — before a human ever sees it.
- 600+ pre-built detection rules mapped to MITRE ATT&CK
- Behavioral baselines per user, device, and service account
- Sub-60-second detection latency from log ingestion to finding
Detection that never sleeps
Autonomous triage with structured verdicts
The Triage agent answers a 12-question evaluation protocol for every finding: is the entity known-bad? Is the behavior novel? Is the timing anomalous? The output is a confidence-scored verdict, not a raw event dump.
- True-positive confidence score from 0–100 per alert
- Evidence package with IP reputation, domain age, entity timeline
- Auto-closed false positives documented with rationale
Autonomous triage with structured verdicts
Human governance at every escalation
Analysts receive pre-triaged escalations, not raw alerts. Every case includes the full evidence chain, recommended actions, and configurable approval gates before any containment action executes.
- Approve-gate any action class: isolate, disable, block
- On-call routing based on severity and schedule
- Complete decision audit trail for compliance
Human governance at every escalation
What AI SOC delivers
Concrete outcomes security teams measure in the first 90 days.
95% reduction in analyst time per alert
Triage and enrichment are fully automated. Analysts review verdicts and approve actions, not raw log dumps.
Mean time to detect under 60 seconds
Continuous telemetry processing means threats are found in near-real-time, not the next morning's batch job.
Zero alert queue backlog
Every alert receives a disposition — true positive, false positive, or escalated — before it hits the analyst queue.
Operates 24/7 without a night shift
AI agents handle nights, weekends, and holidays autonomously. Humans are escalated to, not paged for everything.
Full audit trail per case
Every detection, triage decision, and response action is logged with timestamps and the agent's reasoning chain.
Deploys in days, not quarters
Pre-built connectors for the 150 most common security data sources. First alerts flow in under two hours.
What security leaders say about AI SOC
“Attack-chain reconstruction turned a 4-hour investigation into a 10-minute review. The case arrives already assembled.”
Victor Nkemelu
Incident Response Lead, Vantagrid
“The triage agent closed 80% of our queue with verdicts we could actually audit. My tier-1 analysts now do tier-3 work.”
Maya Lindqvist
CISO, Northwind Bank
“Dry-run workflows sold our change board on automated response. We see exactly what would happen before granting autonomy.”
Daniel Okafor
VP Security Operations, Cobalt Health
AI SOC — common questions
What makes this an 'AI SOC' vs a traditional SIEM with rules?
A traditional SIEM surfaces raw events and counts on analysts to triage them. The ManySignal AI SOC adds a triage agent that evaluates every finding with a structured protocol, generates a confidence-scored verdict, and builds the full evidence package before any human sees the alert. The analyst's first interaction is with a decision-ready case, not a raw event stream.
Can we choose which actions the AI takes autonomously vs. which require approval?
Yes. The autonomy ladder lets you configure per-action-class policies: fully autonomous, approval-gated, or recommend-only. You can allow the AI to auto-block known-bad IPs while requiring human approval to disable a user account. Policies are explicit, audited, and revocable at any time.
How does ManySignal handle false positives?
The triage agent auto-closes findings it assesses as false positives with a documented rationale — the rule that fired, why the evidence doesn't support escalation, and the entity history that informed the decision. Teams typically see 85–95% of findings auto-closed within 90 days as behavioral baselines mature.
What data sources does the AI SOC connect to?
ManySignal ships 150+ connectors covering cloud providers (AWS, Azure, GCP), identity (Active Directory, Okta, Entra ID), endpoint (CrowdStrike, SentinelOne, Microsoft Defender), network, and SaaS applications. Custom sources can be added via webhook or the OpenTelemetry collector.
How long does deployment take?
Most customers complete initial connector setup and first detections in under two hours. The full onboarding program — data source coverage, baseline training, detection tuning, and analyst workflow integration — runs over four weeks and is included with every subscription.
How is the AI SOC different from hiring a managed detection and response (MDR) provider?
An MDR provider gives you a third-party team operating tools you may not have direct visibility into. ManySignal gives you an AI SOC that operates inside your environment with full transparency — every triage decision, every evidence item, and every action is visible to your team. You retain complete control over autonomy policies, and your analysts are empowered rather than replaced. MDR tends toward opacity; ManySignal tends toward analyst augmentation with full audit access.
What happens to in-progress cases if ManySignal experiences downtime?
Open cases are preserved with all evidence, agent reasoning, and action history. Upon recovery, agents resume processing the queue from where they left off. For active incidents, the on-call notification (Slack, PagerDuty) includes the last known state of the case and pending actions so analysts can proceed manually if required. ManySignal's core pipeline maintains a 99.9% availability SLA.
Can the AI SOC operate in a self-hosted deployment for data sovereignty requirements?
Yes. ManySignal's self-hosted deployment via Helm chart supports all five agents operating on customer-managed Kubernetes infrastructure. In self-hosted mode, all telemetry, entity graph data, and AI model inference remain within the customer's environment. The self-hosted deployment supports the same autonomy ladder, detection engine, and response integration capabilities as the cloud-hosted version.
How does ManySignal prevent the AI from taking actions based on poisoned or manipulated telemetry?
ManySignal's guardrail layer includes telemetry integrity checks: detection of log deletion or modification events, validation of event timestamps against collection time, and monitoring of connector health for anomalous data drops. Blast-radius limits cap the scope of any single automated response action regardless of how high the confidence score. The kill switch allows global autonomy to be disabled in seconds if unexpected behavior is observed. These controls are designed to prevent both accidental and adversarially induced runaway automation.
See the AI SOC handle a real alert queue
Book a 30-minute demo. Bring your noisiest data source — we'll show you triage verdicts, evidence packages, and confidence scores on live-looking alerts.