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06 / 08 · built · 2026 · MVP

GTM-Zero

AI sales engineer for technical founders: live objection handling with citation-grounded answers.

Role
Solo founder: Spring Boot and Spring AI backend, Next.js and React frontend, retrieval pipeline, streaming SSE architecture, prompt design, pitch preparation. Shipped in 5 days.
Stack
Java · Spring Boot · Spring AI · Next.js · React · TypeScript · PostgreSQL · pgvector
Links
GitHub

< 2 s

first token on the three demo questions

Source: Measured on the pitch build · as of Oct 2026

GTM-Zero solves the bottleneck that kills most solo technical founders: they can ship a product in a weekend but freeze when a CTO asks how they handle GDPR or what prevents prompt injection on a sales call. GTM-Zero runs on a side monitor during the call. The founder presses a hotkey, the system retrieves the relevant chunks from their own technical docs, and streams a citation-grounded answer in under 8 seconds. Every claim cites a real source. If the AI cannot ground a claim, it refuses, and that refusal is the product.

Built end to end in 5 days: 6 Flyway migrations, custom pgvector mapping, streaming SSE with token-by-token rendering, inline citation validation with regex-based coverage scoring, and a separate personalized outreach generator. The frontend is a split-screen live-call interface that mirrors a video call with the prospect on the left and the streaming answer on the right. Three pitch-ready demo questions return cited answers with first-token latency under 2 seconds and 82 to 100 percent citation coverage.

The system prompt forbids invention, the validator enforces it inline without a second model call, and the frontend renders streaming tokens with citation chips that fade in after completion. Built as the answer to my own problem from REGU: shipping a product was not enough if I could not sell it.