A client needed their customers to be able to query a 40-page policy document without reading through it. We built the first version of what became Minyut in a weekend. It used a basic embedding approach, answered from an OpenAI endpoint, and—in testing—confidently responded to questions that had no answer in the document at all. It made things up. Fluently. Completely wrong. That was the founding problem. Every document chatbot we tested made things up. Not because the models were bad, but because they weren't constrained to answer only from the documents. Minyut is built around a single architectural decision: Every answer must come from uploaded content—or the chatbot says, "I don't know." Everything else follows from that constraint. Today, Minyut processes queries for chatbots embedded on Webflow sites, WordPress installs, Shopify stores, React apps, and plain HTML pages. Documents are stored in Supabase's Mumbai region, and the widget can be embedded with a single script tag in under ten minutes.…