OpenMemory gives AI agents real long-term memory. Not vector search. Not RAG. Actual memory.

Plug-and-play memory for LLMs in 3 lines of code. Add persistent, intelligent, human-like memory and recall to any model in minutes.

Git based Version Control File System for joint management of code, data, model and their relationship.

Distributed data mesh for real-time access, migration, and replication across diverse databases — built for AI, security, and scale.

Stop paying for AI APIs during development. LocalCloud runs everything locally - GPT-level models, databases, all free.

TME: Structured memory engine for LLM agents to plan, rollback, and reason across multi-step tasks.

GPU-aware inference mesh for large-scale AI serving

A curated list of awesome tools, frameworks, platforms, and resources for building scalable and efficient AI infrastructure, including distributed training, model serving, MLOps, and deployment.

Collective AI memory for engineering teams.

Production-ready AI infrastructure: RAG with smart reindexing, persistent memory, browser automation, and MCP integration. Stop rebuilding tools for every AI project.

UniRobot is an embodied intelligent software framework that integrates the robot brain (data, models, model training) with the robot body (perception, model inference, control).

Production-ready infrastructure for AI agents. Deploy, orchestrate, and scale agent workflows with Vercel-like developer experience.

This repository contains a list of various service-specific Azure Landing Zone implementation options.

Secure Computing in the AI age

A modular, self-contained file format for executable AI prompts, logic, and data.

Enterprise-grade LLM routing microservice with multi-provider support, intelligent failover, and cost optimization.

Rent ready-to-use cloud GPUs in seconds. Lium CLI makes it easy to launch, manage, and scale GPU compute directly from your terminal. Fast, cost-optimized, and built for AI & ML developers.

Repo from AWS GenAI workshop—build cost-efficient agentic LLM systems using SageMaker, Bedrock, and Strands.

dot-agent-protocol

The global open standard for governing the lifecycle of intelligent multi-agent systems. MPLP defines the four-layer protocol stack (L1–L4) for planning, execution, observability, and integration— enabling agents, runtimes, and tools to interoperate with the reliability of the Internet.