For analysts
Turn interviews into structured requirements without losing context.
Work a living model, not a stack of transcripts. Generate requirements and user stories that keep a link to the exact evidence behind them, and spend your time on judgment instead of transcription.
From transcript to structure, without the grind
Stakeholders talk in plain language. Bontology structures what they say into activities, issues, and systems as the interviews come in, so you start from a model instead of a blank document and a pile of recordings.
Structure as you go
Every session adds to the same model. You are never re-reading a transcript to remember what someone said three interviews ago; it is already an object with a state.
Nothing dropped, nothing invented
Anything the model does not recognize is flagged and kept, not silently discarded and not guessed into a category it does not belong in.
Fig. 1 · requirement structure
Requirements with evidence attached
Functional requirements and non-functional requirements (NFRs) are both first-class, following ISO/IEC 25010's quality characteristics: performance, security, reliability, usability, and the rest. Every requirement, of either kind, carries a trace link back to the evidence it came from.
Fig. 2 · analyst workflow
User stories that carry business context
A story generated from the model does not arrive stripped of context. It carries the activity it replaces, the issue it resolves, and the dollar figure behind it, so a developer reading it later understands why it exists, not just what to build.
solution → story
OCR intake · 4.2x ROI · 7-mo payback
$86,300 /yr estimated benefit
Generated from the packing-slip re-entry issue at Hartwell Fabrication Co. (sample model): five acceptance criteria, a trace link back to the warehouse interview line that first described the problem, and the ROI math behind why it is prioritized where it is.
Work the exception queue
Low-confidence classifications and anything the model could not resolve on its own route to you, not into the numbers unchecked. You adjudicate, and your judgment is recorded against the item, not lost in a comment thread.
Confidence-scored, not black-boxed
Every AI-generated item states how sure it is. You can see exactly why something needs a second look before you look at it.
Your call, logged
When you agree, disagree, or reclassify, the reasoning is captured alongside the item for anyone who reviews it later.
Verify and certify
Requirements and stories move through the same verification ladder as everything else in the model: Estimated, Verified, Certified. Every state change is timestamped and attributed in the audit trail, so a certified item is defensible, not just labeled.
Hand off in the build partner's language
Requirements and stories export in formats the build team already uses, with the business context and the trace link intact, so nothing gets re-explained or re-typed on the other side of the handoff.
See the model an analyst actually works in.
A short conversation, then a guided assessment. Your model stays yours.