RuVix

Core library for AI agent routing using FastGRNN in the RuVector ecosystem. Enables efficient semantic routing for multi-agent AI systems with low resource footprint, suitable for vector database-integrated workflows.

Rust crate for proof-carrying vector operations using lean-agentic dependent types, providing formal verification with ~500ns proofs for secure vector computations in AI systems.

Rust-based PostgreSQL extension accelerating vector similarity search with diskless HNSW (20x faster than pgvector), DiskANN indexes, and hybrid SQL for ANN on embeddings. Enables FP16/INT8/binary vectors with ACID compliance; perfect for high-throughput RAG in DB, real-time analytics. Superior speed/resource efficiency vs dedicated vector stores like Weaviate, all within Postgres.

An advanced RAG architecture where an AI agent autonomously decides which questions to ask, which tools to use, when to retrieve information, and how to aggregate results. Represents a major trend in 2026 for more intelligent and adaptive retrieval systems.

Open-source LLM app development platform with an intuitive interface that combines AI workflow, RAG pipeline, agent capabilities, model management, and observability features for rapid prototyping and production deployment.

Knowledge engine for AI agent memory and memory layer for AI agents. Replaces complex RAG pipelines with serverless, single-file memory supporting instant retrieval and long-term memory.