How We Built a Real-Time RAG Application for Free With SingleStore and Vercel

We're building a modern real-time AI app that provides recommendations on which Large Language Models (LLMs) are most suitable for specific use cases based on the latest data, sentiment, and scores. The app uses SingleStore's Notebooks and Job Service to bring in real-time data from various sources, enrich it with vector embeddings, and ensure it's queryable by downstream LLMs and applications. We've used Twitter, Reddit, and GitHub APIs to gather raw data for each model, and then searched for this data using the SingleStore Elegance SDK and Vercel. The app queries this data using RAG (Real-Time RAG) and provides recommendations based on user input. This demonstrates how a single developer platform can host hybrid free database + cloud services, making it easy to build modern AI apps with real-time capabilities.

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