simd

CPU-first, eager-execution tensor/autograd runtime and LLM inference engine written in pure Zig

PostgreSQL TurboQuant Index for PGVector

This project implements 30+ variants of ANN algorithms to find the K nearest neighbors in high-dimensional vector spaces. It is meant as a convenient sandbox: drop in your own ANN code, run a one-liner, and instantly compare build/search speed and recall against the bundled baselines.

sovereign embedded vector database, single-file .nest container with content-addressable citations, reproducible builds, and offline-first model verification.