Software-delivery reliability, AppSec prioritization, supply-chain protection and secure release automation.
Talk to a DevSecOps AIOps Specialist
Each service can be taken alone. They share telemetry, policy and runbooks when combined.
Classify pipeline failures, spot flaky and transient issues and recommend safe recovery.
Example scenario
Trigger different pipeline failures and show classification plus a safe retry.
Deduplicate and rank SAST, DAST, dependency, container and IaC findings by exploitability and context.
Example scenario
Ingest several scanner outputs and produce one prioritized developer backlog.
Track SBOMs, provenance, artifact signatures, dependencies and build integrity.
Example scenario
Introduce an unapproved dependency or unsigned artifact and block the build.
Combine tests, security, IaC policy, live SLO health and change risk into one governed release gate.
Example scenario
Compare a healthy release with a risky one and show different promotion outcomes.
Find exposed secrets and excessive permissions across code, CI/CD, Kubernetes and cloud configuration.
Example scenario
Commit a fake secret and a broad RBAC change, then detect and safely remediate both.
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