Savvina – Text-to-SQL Query Tool

A self-hosted, privacy-focused AI tool that converts natural language questions into SQL queries, eliminating repetitive data requests for data teams. Solves the problem of analysts spending time on one-off queries from scattered requests.

The text-to-SQL space is heating up precisely because LLMs have finally crossed a threshold where they can handle joins, subqueries, and dialect-specific syntax with reasonable accuracy — making 2024-2025 a credible window to ship something production-grade rather than a demo toy. The closest incumbent is Defog (and to a lesser extent, tools like Outerbase and AI2SQL), all of which compete on the self-hosted, privacy-first angle, meaning differentiation will need to come from integration depth or workflow fit rather than the privacy pitch alone. The $2k–10k/mo revenue band is plausible for a dev-tools product selling to data teams at mid-size companies on per-seat or usage pricing, but it assumes someone actually pays rather than rolling their own with a GPT-4 API wrapper and a few prompt engineering hours. The biggest risk is exactly that: the build-vs-buy calculus is brutal here, since a competent data engineer can replicate the core functionality in a weekend, so without strong schema-awareness, access controls, or workflow integrations, there's no durable moat.