SqueelGPT

We are a group of Master students all studying, working or researching in the IT domain and noticed two trends that interested us. Larger companies like Uber, Amazon, and Salesforce all published some kind of Text-2-SQL paper or model for internal use, and the first AI startups with similar solutions started launching. However, we noticed that either the published models had weaknesses in accuracy and efficiency, while the startup solutions did not correctly target the users who would benefit most from such solutions: enterprises with large, complex databases. Enterprises face fundamentally different challenges compared to small companies. They deal with dozens of databases, massive tables with millions of records, complex constraints and relationships, and hundreds of daily requests to retrieve information. This is where SqueelGPT can make a real difference. We built a proprietary dual-phase pipeline that deeply understands database schemas and learns from every query to deliver not just correct, but also optimized SQL for large-scale operations. What sets us apart is our enterprise-first approach. While general AI chatbots like ChatGPT achieve only 38% accuracy on complex SQL benchmarks, our specialized pipeline targets over 95% accuracy through schema-aware processing and semantic understanding. We support all major SQL dialects, provide sandboxed execution environments for safety, and offer both intuitive chat interfaces and robust APIs for seamless integration into existing enterprise tools. Our mission is simple: democratize data access across organizations. Whether you're a business analyst who needs quick insights, a developer building internal tools, or a data team managing complex queries, SqueelGPT bridges the gap between natural language and your databases. We're currently in beta with early access available through our waitlist, and we'd love to hear your thoughts on how AI can transform enterprise data interaction.