Python

GraphRAG that runs entirely in PostgreSQL — pgvector for vectors, recursive CTEs for graph traversal, tsvector BM25 for keyword search. No graph database, no second backup strategy, no data sync.

Sub-millisecond extractive summarization with byte-identical Python and Rust implementations. The preprocessor that sits in front of the LLM call and cuts tokens 40-94 percent.

Sub-millisecond extractive summarization with byte-identical Python and Rust implementations. The preprocessor that sits in front of the LLM call.

Standalone ingest-to-pgvector with a built-in chunker × embedder bakeoff. One YAML config = one end-to-end ingest cell. Python + Rust at parity.

Runnable sample app: Postgres 16 with Apache AGE and pgvector, a FastAPI orchestrator, and four retrieval strategies compared side by side on 391 real SCOTUS cases.

Scripts to test and benchmark JSON functionality across MySQL, PostgreSQL, and MongoDB — and generate simulated load.

Local-first MCP server that indexes code and docs into Postgres + pgvector for hybrid retrieval by LLM coding clients.

A top-like live terminal dashboard for monitoring LLM inference servers on NVIDIA DGX Spark.