landingbj/LinkMind

What it solves

LinkMind is an enterprise-grade AI middleware layer designed to eliminate the need for business systems to integrate with multiple AI providers individually. It provides a stable, unified interface for chat, RAG, and multimodal capabilities, reducing the friction of onboarding new models and managing production governance.

How it works

It acts as a centralized hub that sits between business applications, private knowledge bases, and AI model providers. It exposes both native and OpenAI-compatible APIs to handle requests for text, audio, image, and video. The system uses a configuration file (lagi.yml) for central routing, failover, and orchestration, and integrates with various vector stores for RAG. It also supports a "Token Grid" architecture, allowing multiple LinkMind nodes to be linked in a cascade network to share compute and domain capabilities while maintaining data isolation.

Who it’s for

It is built for teams and enterprises that need a production-ready AI infrastructure to manage multiple LLMs and multimodal models, integrate private data via RAG, and connect existing agent runtimes like OpenClaw or Hermes Agent.

Highlights

• Unified Multimodal API: Single layer for chat, OCR, ASR/TTS, image/video generation and understanding, and text-to-SQL.
• Multi-Model Orchestration: Centralized routing and failover (via best() and pass() routers) to avoid provider-specific code rewrites.
• Enterprise RAG: Direct connection to vector stores like Chroma, Milvus, Pinecone, and Elasticsearch, with graph-style augmentation.
• Production Governance: Includes Medusa cache acceleration, token statistics, and centralized security guardrails.
• Agent Runtime Sync: Built-in hooks for seamless integration with OpenClaw, Hermes Agent, DeerFlow, and OpenHuman.
• Token Grid: A cascade network topology where nodes act as both consumers and providers of AI capabilities.