AI Requirements Analysis & User Story Automation
From meeting notes to clear user stories—with gap analysis and prioritization for a smooth project start.
Clarity From Conversations
Meeting notes become structured requirements and acceptance criteria.
Fewer Surprises
Automatic gap detection highlights missing pieces and risks early.
Faster Handover
Prioritized stories are ready for immediate delivery to dev teams.
What is the challenge?
Requirements engineering is time‑consuming and error‑prone. Unstructured workshops, interpretation gaps between business and IT, and manual transfer into user stories cause misunderstandings and delays. Requirements Analysis needs to be faster, complete, and auditable.
What is the solution?
An AI‑powered requirements assistant analyzes transcripts, detects gaps and risks, and automatically generates structured requirements and user stories (incl. acceptance criteria) for Jira, GitLab, and more.
- Analytical extraction: Functional/non‑functional reqs, priorities, scope, risks.
- Strategic packaging: Executive dossiers with business value and cost‑benefit.
- Operational translation: Ready‑to‑ship stories with Gherkin criteria and one‑click export.
Real‑world use cases
- Kick‑off workshop: Gap analysis (e.g., “missing authorization model”) and clear question list.
- Pre‑sales: Auto‑generated client dossier with business‑value estimate for go/no‑go decisions.
- Backlog refinement: 20+ syntactically correct tickets with acceptance criteria at the push of a button.
Why invest now?
- Up to 80% faster project start: From conversation straight to the backlog.
- Higher quality: Standardized, complete stories instead of interpretation errors.
- Risk reduction: Gaps, contradictions, and cost traps surface early.
- Clarity for executives: Data‑driven dossiers replace gut feeling.