Reckon is a private product I’m building to help businesses understand how AI search represents and recommends them. I work directly with clients on their audits and reports, with access arranged through a conversation.
What it helps answer
- Does the business appear when people ask AI search for recommendations?
- Which competitors appear in those answers?
- What sources do the answers cite?
- What website fixes and content opportunities are worth investigating?
An audit reviews a defined set of questions on ChatGPT and Perplexity. Reports connect findings to the saved answers and cited sources, so clients can look beyond a summary number and inspect the evidence behind it.
What I’m building
I’m building the audit pipeline and reporting dashboard: business-profile setup, question review, answer collection, competitor comparisons, source analysis, and prioritized recommendations. Clients can review the findings, track progress on recommendations, and share website-fix briefs with their developers.
The backend uses Python, FastAPI, and Postgres. The dashboard uses Next.js and TypeScript. My focus is making the results understandable and traceable, including showing when an audit has incomplete data.
Each audit is a snapshot of specific questions, engines, and a chosen market. Recommendations are investigation leads; they do not guarantee a change in AI visibility.
Private access
Reckon is privately operated. The app, source code, and client reports are not publicly shared.