Answerify

'Where is the source for this?' is the primary bottleneck for support teams. They spend nearly half their shift performing knowledge archaeology — hunting through siloed documentation and past threads to answer repetitive queries. Manual retrieval leads to slow responses, inconsistent advice, and a significant drafting tax.

An AI-driven support inbox that converts static knowledge bases into automated, verifiable responses. A confidence scorer decides between Autopilot (auto-reply if >65%) and Draft mode (human review). A continuous learning loop integrates manual edits back into the knowledge base to sharpen future accuracy.

• A customer asks a question via email
• Answerify parses the email and identifies the context
• The system queries the knowledge base via RAG and synthesizes a cited reply
• If confidence > 65%, Autopilot replies directly; otherwise, a draft is queued for the support team
• Edits flow back into the knowledge base to improve future answers

• Ingestion agent — scrapes, chunks, and embeds documentation URLs
• Response engine — synthesizes thread history and RAG results into cited replies
• Confidence scorer — heuristic engine choosing Autopilot vs Draft

• Stack: Node, Next.js, Supabase (DB + vector search)
• Email infra: Cloudflare
• LLM: OpenAI
• Vibe coding: Cursor, Copilot, Claude, ChatGPT