DGi

How did a team of 4 research engineers beat $100B labs like OpenAI and Anthropic in establishing the best coding agent? It starts with having a killer engineer on your team. In our case, we have @_AbhaySinghal 🧵

About three months ago we launched DGi (dgintel.ai), a data agentic system. IT SUCKED, like all agentic systems do right now when it comes to data analytics. Just a few weeks ago, I used one of the big AI players to vibe code a data dashboard. A few days later, I realized it was completely wrong. That’s the hard part about AI, we’re starting to rely on it so much that we end up living inside its hallucinations. What we need are systems we can trust. That’s the real challenge. Customers loved the idea behind DGi, but they told us it was unusable: too slow, inaccurate, and hard to rely on. The concept was right, but the execution wasn’t there yet. We went back to the drawing board and decided that to make something people actually use, we had to: Make it fast. Make it secure. Make it accurate, and give ourselves a way to measure that. Specialize it with the right tools for real data analysis. Today we’re announcing DGi v2, along with a performance evaluation comparing DGi to four other companies on real data analytics tasks (Replit, v0, Claude and OpenAI). You can see the summary of the results in the comments and in the image attached the overall benchmark. DGi v2 now includes double envelope encryption, encryption on top of encryption. When you connect your database, your credentials go through two layers of protection. We also trained DGi using gold-standard data science practices so it can better handle edge cases, large datasets, and more. And we’re adding features like scheduling (coming next week), code editing, and a metadata store (credential storage), so AI can help, but you can step in and take control when needed. We’re still far from where we want to be. Next up: dashboard creation and deployment. But this version is a solid foundation to start exploring and analyzing your data with a high level of accuracy and reliabillity. Right now, DGi is somewhere between ChatGPT, Airflow, and Replit, but with deep data specialization. Our models are trained with data analysis best practices and include data reviews on final responses. We hope you’ll keep supporting us on this journey. We imagine a future without Excel files, Power BI, or Tableau dashboards. That future isn’t easy to build. Reliable and accurate agentic systems are complex to build. But we’re leading the way.