#embeddings

AI sovereignty for the world's most trusted runtime.

Official Rust Implementation of Model2Vec

Persistent memory & RAG engine for AI agents — SQLite + FTS5 + embeddings, multi-stage recall, sleep maintenance, multi-host hooks

Ship the App, not the Plumbing. Built on Axum.

.NET library for on-demand local AI model inference — zero bundled models, lazy loading, hardware-aware GPU/CPU selection, 10 task types including embeddings, generation, vision, and audio.

The .NET library to build AI agents with 30+ built-in connectors.

Embedding-based code duplication detector

Deep code indexing MCP server for AI agents. 25 tools: hybrid FTS5 + embedding search, call graphs, git blame/hotspots, build system analysis. Multi-repo workspaces, GPU-accelerated semantic search, 10 languages via tree-sitter. Fully local, zero cloud dependencies.

QNTX = Experiential ꩜ Learning ⌬ System ≡ Attestation +

C# SDK for the Jina API -- embeddings, reranking, and search

Semantic + structural code search for AI-native development

Reflective memory for agents

Search code and feature records by meaning through the command line or Model Context Protocol (MCP). Inference runs on your GPU.

Persistent memory for AI agents

Declarative SQL query engine for Qdrant and edge vector databases. Multi-vector dense & BM25 sparse search, hybrid retrieval, CTEs, and MMR in Rust, Python, Node.js, and WebAssembly

Semantic memory for AI agents — local-first MCP server with hybrid search, governance, and consolidation

Retrieval and Retrieval-augmented LLMs

swarmdo — self-contained AI agent orchestration for Claude Code (swarmdo.com)

A pure-Go, single-file AI memory and knowledge graph library and plugin.

Self-hosted retrieval infrastructure for AI assistants. MCP-first search and grounded answers over a private corpus, with citations that resolve to a real location in a real document — a page, a heading, a line, a cell.

Code search that lets AI coding agents find the right files in fewer steps. Use the hosted endpoint or self-host, works with Claude Code, Copilot and Cursor via MCP.

The RAG pipeline that grows with your codebase — index once, stay in sync with every commit.

zvec rust binding

Claude code memory, or maybe not code.

AI-Lake Format: self-contained Parquet + HNSW index — unifying tabular data, embeddings, and vector search in a single Iceberg-compatible file

Production-ready .NET 10 RAG library with hybrid vector + keyword search, multi-backend storage (SQLite, PostgreSQL, Neo4j, Qdrant), and MCP server integration.

Orquestador multi-agente de CLIs de IA para pipelines RAG

RushDB is a graph + vector database and memory layer for AI agents. Push any JSON, get typed, searchable, relationship-aware records back — no schema, no migrations. Built on Neo4j.

ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector

Graph memory for AI agents: facts in, entities and cause->effect relations extracted with small open models, multi-hop recall with a cited chain. Library, HTTP/MCP service, LangChain, hosted at memory.primaxiom.ai