Built QueryWeaver, an open-source text2SQL tool that uses a graph to create a semantic layer on top of your existing databases. When you ask "show me customers who bought product X in a certain ‘REGION’ over the last Y period of time," it knows which tables to join and how. When you follow up with "just the ones from Europe," it remembers what you were talking about.

Instead of feeding the model a list of tables and columns, we feed it a graph that understands what a customer is, how it connects to orders, which products belong to a campaign, and what "active user" actually means in your business context. We used FalkorDB for the graph part because it handles relationship mapping better than cramming table schemas into prompts. Graphiti tracks the conversation so follow-ups actually work. Final notes: Your data stays in your databases. We read from existing schemas, never migrate data. Standard SQL outputs you can run anywhere. We've built an MCP and you can generate an API key to take it for a spin. Please, tell us how it’s working out for you!