How it works
Follow one customer signal through the loop.
Annsa turns customer feedback into ranked priorities and codebase-aware specs, then tells the customers who asked. The same evidence stays attached the whole way.
One loop. Evidence stays attached.
The handoff is the product: signal becomes judgment, judgment becomes build context, and shipped work returns as evidence.
See the loop inside the product.
Priorities ranked in the middle, the spec they became on the right, every number tracing back to the customers who asked.
What happens at every handoff.
8 sources land in one evidence layer: Slack, in-product surveys, call transcripts, CSV, Google Sheets, Reddit, manual entry and an API. Slack polls every 10 minutes. Customer names, emails and phone numbers are stripped before any AI call, and the original wording stays attached.
Related feedback groups into priorities, scored across 6 dimensions: volume, urgency, revenue, positive sentiment, negative sentiment and feature demand. Ranking weights company spread, so repeated requests from one account do not drown out a pattern across many customers.
One cited artifact with 5 sections: What to Build, Why It Matters, Customer Voice, Files to Touch and Done When. Connect a repository and Annsa reads 9 GitHub signals, so Files to Touch only names paths that exist. It reads the codebase. It does not write code.
4 tools over MCP: annsa.priorities, annsa.spec, annsa.ask and annsa.act. Nothing to install. Cursor and Claude Code pull the ranked work and the grounded spec straight into the editor, so nothing is copy-pasted out of a browser.
Mark it shipped and the share-back opens with the recipients already assembled, their own words quoted back to them. Review it, then send by email, survey banner or both. New feedback on the same theme feeds a V2 spec.
The evidence, the spec, the answer.
See priorities from your own customer feedback.
Annsa runs the intelligence. Your team and agents run the build.