aiSOC is a multi-tenant, AI-powered triage platform that gathers evidence, reaches a defensible verdict, and hands your analysts only the cases that genuinely need judgement.
Deterministic verdicts · full audit trail · analyst always in control
Security teams are buried in high-volume, low-context alerts. Triage is manual, inconsistent between analysts, and the knowledge from every closed investigation walks out the door with the analyst who worked it.
Every alert flows through the same pipeline: ingested from your SIEM, classified, risk-scored, enriched with evidence and host history, and given a deterministic verdict with a calibrated confidence score.
Alerts arrive by webhook or scheduled pull and are normalised to one canonical schema — whatever the source.
Heuristic + ML classification, a 0–100 risk score, and MITRE ATT&CK technique mapping, within milliseconds.
Telemetry extraction, SIEM corroboration, 30-day host history, similar past cases, threat-intel reputation and historical FP rates.
A transparent rule engine maps the evidence to one of six verdicts with a confidence score — and shows exactly why.
Related alerts group into cases with an attack graph and timeline. Optional auto-closure and containment sit behind explicit, off-by-default switches.
Connects to: Rapid7 InsightIDR · Splunk · Microsoft Sentinel · CrowdStrike Falcon · any webhook or API source via the built-in source-mapping engine · Jira Cloud · Slack / Teams / Google Chat
Most "AI security" is a score you're asked to trust. aiSOC is built the other way round: every decision is deterministic, inspectable, reversible — and always subordinate to your analysts.
Same evidence, same verdict, every time. The rule that fired, the signals used and every confidence adjustment are recorded and shown.
Auto-closure and response actions are off by default, gated per action, fully audited and reversible. The engine never overrides a human decision.
Source-agnostic normalisation means no vendor lock-in. New sources are a mapping, not an engineering project.
Strict tenant isolation at the authentication boundary, per-tenant SSO, break-glass recovery, and per-client configuration throughout — built for MSSPs from day one.
Historical false-positive rates, host history and weekly retraining from analyst verdicts calibrate the engine to your estate — not generic assumptions.
Local embeddings and classical ML on standard infrastructure. No GPU farm, no alert data shipped to third-party model providers.
Cut the queue down to the cases that need judgement. Every investigation arrives pre-enriched with the same depth of evidence, gathered identically every time.
Run every client on one platform with hard tenant isolation, per-tenant SSO and connectors, and a fleet view across your whole estate.
Adopt automation incrementally, with a complete audit trail, dual-control approvals and per-action kill switches you can show to auditors and the board.
A look at the console — the inbound triage queue, the autonomous analysis card, and correlated cases with their attack graph. All demonstration environments use synthetic data.
The fastest way to understand aiSOC is a walkthrough — 30 minutes, live platform, your questions. Tell us a little about your environment and we'll set it up.
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