Building a Production-Ready Safe-AI Gateway: Policy as Code, Semantic Caching, and Human-AI Collaboration

As the enterprise adoption of Generative AI (LLMs) accelerates, IT and software engineering teams face three critical structural challenges: security & privacy enforcement, mitigation of hallucinations (grounding), and resilience against cloud API outages or throttling.

Rather than relying on manual rule management or speculative guidelines, this reference implementation resolves these challenges through infrastructure and structure (Policy as Code + Gateway Architecture).

Key Components & Architecture

The system integrates an asynchronous FastAPI gateway, Amazon Bedrock Guardrails, and Redis Stack (Vector Search) to establish a self-healing, multi-layered defense model.

  • Policy as Code Governance: Guardrail definitions are managed as code in YAML and automatically deployed to AWS Bedrock via GitHub Actions with OIDC authentication.
  • Zero-Downtime Resilience (Circuit Breaker + Semantic Cache): During AWS API throttling or outages, a circuit breaker trips and Redis HNSW vector search delivers high-similarity historical responses within milliseconds.
  • Contextual Grounding: Factually incorrect or ungrounded model outputs are blocked automatically at the API boundary.

Open Source Repository

The complete codebase—including FastAPI application logic, Docker Compose manifests, Terraform IaC, and GitHub Actions CI/CD workflows—is open-sourced on GitHub.

👉 GitHub Repository: https://github.com/Koyano693/open-safe-ai-gateway

We hope this implementation serves as a robust foundational reference for teams building secure, autonomous, and human-centric AI collaboration systems.

Open Safe-AI Gateway

A Production-Ready Reference Implementation for High-Availability & Self-Governing AI Infrastructure via Policy as Code and Semantic Caching.

License: MIT
Python 3.10+
FastAPI
AWS Bedrock

💡 Overview

As enterprise adoption of Generative AI (LLMs) accelerates, software engineering teams face three critical structural challenges:

  1. Security & Privacy Risks: PII leakage, prompt injection, and unauthorized data access.
  2. Hallucination & Governance: Unreliable responses and rigid, manual compliance management.
  3. Resilience & Availability: Cloud API throttling (HTTP 429) and upstream service outages.

Open Safe-AI Gateway addresses these challenges through infrastructure, facts, and structure rather than speculative assumptions. It provides a multi-layered, zero-trust defense gateway integrating FastAPI, Amazon Bedrock Guardrails, and Redis Stack (Vector Search).

🚀 Quick Start (Docker Compose)

1. Clone the Repository & Setup Environment

git clone [https://github.com/Koyano693/open-safe-ai-gateway.git](https://github.com/Koyano693/open-safe-ai-gateway.git)
cd open-safe-ai-gateway
cp .env.example .env