A comprehensive toolkit for deploying production-ready Generative AI infrastructure on Amazon EKS. Includes pre-configured components for: 🚀 AI Gateway (LiteLLM) 🤖 LLM Serving (vLLM, SGLang, Ollama) 📊 Vector Databases, 🔍 Embedding Models (TEI) 📈 Observability (Langfuse, Phoenix) etc. Fast-track your GenAI deployment with Kubernetes

A minimal yet powerful framework for creating AI agents with full control over tools, providers, and execution flow.

End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.

Open Source A2A Protocol Adapter SDK for Different Agent Frameworks and Harnesses

A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.

Fastest enterprise AI gateway (50x faster than LiteLLM) with adaptive load balancer, cluster mode, guardrails, 1000+ models support & <100 µs overhead at 5k RPS.

Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.

Model Context Protocol (MCP) Gateway & Registry - Central hub for managing tools, resources, and prompts for MCP-compatible LLMs. Translates REST APIs into MCP, builds virtual MCP servers with security and observability, and bridges multiple transports (stdio, SSE, streamable HTTP).

An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management. Optimizes Agent & Tool calling, and supports plugins.