RAG-LCC – config-driven RAG framework for fast experimentation

RapidFire AI: Rapid AI Customization from RAG to Fine-Tuning

I built VectorLens because I was tired of "log file archaeology" every time my RAG pipeline hallucinated. Usually, when an LLM gives a wrong answer, you're stuck guessing which retrieved chunk misled

AI-powered feedback widget for Next.js — users chat with AI, feedback becomes GitHub issues, an autonomous agent implements them, and the system learns from its own failures.

json2vec turns nested, ragged data into neural representations. It lets users define typed schemas: numbers, categories, sets, dates, entities, text, etc., then trains models for prediction and embeddings. The library supports MLM-based pretraining workflows, mutations, and serving. It is built for data that does not fit cleanly into flat tables.