AI Agent Skills

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.

JVector: the most advanced embedded vector search engine

A high-performance observability data pipeline.

RuVector is a High Performance, Real-Time, Self-Learning Ai, Vector GNN, Memory DB built in Rust.

Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requir…

Coordinate multi-agent teams for software and product work

A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.

🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.

A query and indexing engine for Redis, providing secondary indexing, full-text search, vector similarity search and aggregations.

HelixDB is an OLTP graph-vector database built in Rust.

PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control

AI-native HTAP database with Git-for-Data and built-in vector search, serving as the data and memory backbone for intelligent agents and applications.

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

Essential skills for autonomous agents