schmitech/orbit

What it solves

ORBIT bridges the gap between AI models and private enterprise environments. It solves the complexity of connecting LLMs to fragmented data sources (like SQL databases, files, and APIs) and provides the necessary production-grade governance—such as authentication, rate limiting, and observability—that simple chat interfaces or basic model routers lack.

How it works

ORBIT acts as a centralized backend API that sits between your applications and your AI resources. It uses YAML-defined adapters to connect to various data sources (vector stores, databases, REST/GraphQL APIs) and tools (via the Model Context Protocol). It exposes an OpenAI-compatible endpoint, allowing you to route requests to local models (via Ollama, llama.cpp, vLLM) or cloud providers (OpenAI, Anthropic, Gemini, etc.) while managing security and metrics through an admin panel.

Who it’s for

• Developers building AI applications who need a production-ready backend with built-in authentication and observability.
• Enterprises looking to connect private data (spreadsheets, PDFs, databases) to LLMs securely.
• Engineers needing to manage multiple AI providers and local models through a single, governed API contract.

Highlights

• Unified API: Provides an OpenAI-compatible interface for models, data, and tools.
• Extensive Connectivity: Supports files, SQL, NoSQL, vector stores, and MCP tools.
• Production Controls: Includes RBAC, SSO, quotas, moderation, and audit logs.
• Hybrid Deployment: Can run locally (offline) or in the cloud with support for both local and cloud-hosted models.