A sales intelligence system that learns from every call

What I built

A sales-prep system the company's sales lead uses on every active deal. It isn't an app or a website — there's nothing to log into, host, or maintain. It runs as a set of AI routines inside the tools the team already works in (Claude and Notion).

• Research and prep. Paste a website, email, or company name and, in about two minutes, a prep sheet is ready. The system reads the prospect's whole website (skipping dead links), checks their social profiles and directory listings, works out how well they fit as a customer, detects which competing tools they already use by reading the code of their site, and writes it all up — grounded in a curated library of the company's own sales knowledge.
• A clear recommendation. Every prospect gets two simple ratings — how well they fit, and how worth pursuing they are — which combine into one of four calls: pursue now, play the long game, wrong fit, or pass. Each rating comes with a one-line reason tied to something specific the system found.
• Honest about what it knows. Every fact is tagged confirmed, inferred, or estimated. The system never assumes which tools a company uses — it only says so when it finds real proof on their site. Every brief arrives marked needs a quick review, and shaky ones carry a warning at the top. A blank field beats a made-up one.
• Catches bad-fit deals early. It automatically flags the warning signs that make a deal a poor fit, and lowers the score when it sees them.
• It learns from every call. Paste the transcript afterward and the brief updates itself — ratings corrected, objections logged, the approaches that worked recorded — plus the one lesson the rep would pass to the next person. That last answer is the most valuable thing the system collects.
• It compiles what's working. Across all those notes it surfaces patterns — labeling each by how much evidence backs it — and, each quarter, rewrites the team's full sales playbook from everything it has learned, including an honest list of what's still unknown.

Underneath it sits a hand-built library of the company's sales knowledge: its features mapped to real customer problems, how it compares to competitors, proven answers to common objections, why customers buy, and patterns from real won deals. The system reads all of it before it writes anything.

Why it matters

The payoff is straightforward: every salesperson walks into every call deeply prepared — the kind of preparation that wins deals, now applied to every deal instead of only the ones someone had time to research. The speed (an hour down to two minutes) is what makes that possible; the loop is what makes it stick. Every call makes the next one smarter, automatically — the system corrects its own judgment, learns which approaches land, and turns that into shared knowledge that no longer depends on any one person remembering. A new salesperson starts with everything the team has learned, not a slideshow.

Normally, "a sales system that learns from every conversation" describes an expensive enterprise product with a team maintaining it. Here it's one person's build, running entirely inside the tools the team already uses.