AI that knows your pipeline inside and out

Connected context, not disconnected data. Links pipeline runs to code, tests, artifacts, and deployments — so AI can answer questions no search box could.

Learns from your patterns. Maps which changes cause failures, which tests are reliable signals, and which deploy patterns correlate with incidents — specific to your team.

Shared context across every AI feature. All AI features — authoring, error analysis, agents, and insights — draw from the same Knowledge Graph and get smarter together.

Context-aware generation. AI reads your repo structure, detects your build system, and generates a pipeline tailored to your codebase — not a generic template.

Best practices built in. Every generated pipeline includes caching, test selection, SBOM generation, and security scan integration — wired in automatically.

Iterative refinement. Ask AI to add a stage, adjust parallelism, or switch infrastructure in plain language. The pipeline updates in real time — no YAML editing required.

Cross-references your entire delivery history. Checks what changed in your code, what dependencies were updated, and whether similar failures happened before — not just the stack trace.

Distinguishes real failures from environment noise. AI identifies whether a failure is a code change, flaky test, infra issue, or dependency bump — so you fix the right thing.

Inline in the build UI. Error Analyzer surfaces in the build details view the moment a stage fails. No context switching to another tool — the answer is right where the failure is.

Generate pipelines on demand. Describe your stack and get a complete, optimized pipeline — language, build system, test framework, registry, and deploy target all configured.

Diagnose any failure instantly. Paste a build URL or ask about the latest failure. Error Analyzer traces it back to the exact commit, config change, or dependency update.

Understand your build costs. Ask where CI budget is going. Pipeline AI breaks down spending by team, pipeline, or stage and surfaces the highest-impact cuts.

Build Performance. Track build times, success rates, and queue depth across every pipeline and branch. Drill into stage-level breakdowns to see exactly where time is lost.

Test Health. Monitor flaky test rates and coverage trends across all repos — with visibility into the slowest tests and Test Intelligence savings.

Cost & Usage. See where CI credits go — by pipeline, team, or stage — and get AI recommendations to cut spend without slowing delivery.