Tech Stack: Java , API Gateway Patterns , Docker & docker-compose
The Problem
Modern AI applications often require interacting with many language model providers (e.g., OpenAI, Anthropic, Gemini). Each provider has a different API, auth method, and behavior , this makes integration messy. AI Gateway solves this by acting as a single entry point that routes requests to multiple providers, handles failovers, caching, rate limiting, and gives consistent responses no matter which provider is used under the hood.
This kind of gateway is useful in AI-powered apps and microservices that need to support many LLM backends without rewriting client logic every time.
Key Achievements
- Unified LLM API interface – One backend endpoint that abstracts calls to multiple AI model providers with a consistent request/response pattern.
- Provider abstraction and routing logic – Handles routing logic so client apps don’t need provider-specific implementations.
- Failover support – Built-in logic to switch providers if one fails (e.g., errors or rate limits).
- Configurable caching & rate-limiting – Reduce cost and latency by caching responses and limiting excessive usage.
- Monitoring & Logging Hooks – Integration points for tracking usage and errors (optional).
- Container-ready with Docker – Provided
Dockerfileand configuration to run this gateway in any Docker-based environment. (repo content
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