AI-assisted threat detection, security-event correlation, behavioral analytics and governed response.
Talk to a Cybersecurity AIOps Specialist
Each service can be taken alone. They share telemetry, policy and runbooks when combined.
Turn SIEM, EDR, cloud, firewall and identity alerts into prioritized incidents with guided response.
Example scenario
Simulate credential abuse plus lateral movement and collapse the raw events into one incident.
Rank vulnerabilities by exploitability, exposure, runtime context and asset criticality.
Example scenario
Ingest many findings and surface the few that are most urgent in context.
Spot suspicious user and service-account behavior against learned login and privilege baselines.
Example scenario
Simulate an abnormal login and a privilege escalation, raise a UEBA incident and respond.
Detect runtime and control-plane threats and apply tightly scoped containment.
Example scenario
Run a malicious-container simulation and quarantine the workload while preserving evidence.
Automate safe enrichment, classification and case creation for suspicious messages, files and URLs.
Example scenario
Submit a simulated phishing message, extract the IOCs and generate an investigation case.
Every service is built as a local-first lab, then extended to your private cloud and to AWS, Azure or GCP.
Ingestion health, processing latency, decisions, automation success and failure, overrides and false positives where measurable.
Validated, allowlisted actions with approval rules and least-privilege identities.
Healthy, false-positive, policy-blocked, automation-failure, rollback and telemetry-source-failure cases, all exercised.
Retained evidence for every decision, a short demo script, and setup, troubleshooting and cleanup documentation.
Rules every AIOps action follows, in every track.
AI output never goes straight to a shell, cloud API or cluster. It selects from validated runbooks.
Disruptive actions wait for a person. Low-risk, reversible steps can run on their own once you agree the rule.
Every action is followed by a health check, with rollback or compensation when the check fails.
Signals, scores, model or rule versions, approvals and results are retained and reviewable.
Adapted to the tools you already run.
Combine tracks to share telemetry, policy and runbooks.
Tell us what you run and where operations hurt most. We will suggest where to begin.
Talk to an AIOps Specialist