Each exhibit below is a real stage in the same pass: a requirements document goes in at the top, and a release comes out at the bottom.
The engine parses uploaded or pasted requirements, separates functional from non-functional detail, and rewrites the result as a structured, Jira-style story.
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Every generated story ships with testable acceptance criteria attached. The same pass assembles a complete PRD — so the spec and the backlog never drift apart.
Stories are estimated against the team's past velocity, not a generic curve. The same pass flags what's still ambiguous — before it turns into a mid-sprint surprise.
Backlog depth, dependency chains, and team history feed a running risk score. A paired health read tracks blockers and pace day by day.
Six sprints of throughput become a projected range for what the team will actually deliver next — visible before planning locks the sprint in.
Completed work is grouped and rewritten in plain language the moment the sprint ends — a drafted release note, ready to review and send.
The AI Engine feeds four surfaces a team already moves through in order — overview, backlog, plan, report.
Upload a doc or write them in directly — no template required.
Stories, acceptance criteria, a PRD, and estimates, generated together.
Adjust, reprioritize, and lock the sprint — the draft is a starting point.
Health, risk, and velocity update daily; release notes draft at close.
Requirements, drafted. Risk, read early. Velocity, forecast — not guessed.