"Anyone can prompt an LLM to summarize notes. We measure and publish whether the summary is actually good — and improve it every week."

Turn raw interview notes into a stakeholder-ready summary in 2 minutes — with synthesis quality we actually measure and publish.

After a 45-minute user interview, PMs spend another 30–60 minutes reformatting notes for Slack, Notion, and leadership. Generic AI hands you an unstructured wall of text you still have to clean up — and you have no idea whether it's any good.

InsightSnap — a synthesis workbench for product managers. Paste raw notes; get tagged pain points, quotes, follow-up questions, and an executive summary; edit before you share; export to Slack, Notion, a leadership brief, or a read-only link. One engine, three profiles (PM Interview shipped; Meeting Recap + Context Brief in beta). A deterministic rule-based engine works with zero API keys; Groq / Llama 3.3 70B layers on for messy notes. Compare mode shows both side by side — not a black box.

A prompt over an LLM is a weekend project. InsightSnap runs a synthesis-accuracy benchmark on every deploy and publishes the live score at /accuracy — quality measurement as a product feature, not a marketing claim. That's the moat, on top of a product that's genuinely shipped end-to-end.

Tech: Next.js 15 (App Router) · Supabase (auth + Postgres + RLS) · Stripe billing · Groq · Upstash rate limiting · Vercel. Solo founder, ~3 weeks. Full CI — lint, typecheck, unit + route tests, coverage gate, benchmark validation. WCAG-checked accessibility; four languages with auto-detection.

Try it https://insight-snap-navy.vercel.app/ → Try InsightSnap → load the Discovery sample → Synthesize → Copy for Slack. See the quality benchmark at /accuracy.

Built With

  • ai-enhanced
  • claude
  • cursor
  • distributed
  • hosting
  • next
  • postgresql
  • pro/team
  • product
  • supabase
  • transactional
  • typescript
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