Sovereign AI Platform with Self-Healing Gateway
Built a self-hosted AI stack that routes, logs, and heals without cloud dependency.
Overview
To ensure operational continuity in air-gapped environments, I architected a sovereign multi-model AI platform. I designed a GitOps control plane using Ansible to orchestrate fleet configuration and automated registry synchronization. The solution included a centralized gateway routing 55 distinct models across a hosted inference provider and local failover nodes. To address agentic risks, I engineered five middleware engines for edge isolation and memory management. Additionally, I implemented a decentralized log ingestion layer using DHTs and magnet links for immutable audit trails. This approach established a single source of truth for infrastructure state while mitigating execution risks in isolated deployments.
Highlights
- 01
Gateway routing 55 distinct models
- 02
5 middleware engines for agentic security
- 03
Decentralized logging via DHT architecture
System Architecture
Data flow from GitOps control through fleet nodes to inference and logging layers.
Questions people ask
- How does the platform handle model routing and failover?
- I built a centralized gateway using LiteLLM to route 55 distinct models across hosted providers and local failover nodes.
- What security measures were implemented for agentic risks?
- I engineered five middleware engines for edge isolation and memory management to mitigate execution risks.
- How is logging managed in air-gapped environments?
- I implemented a decentralized log ingestion layer using DHTs and magnet links for immutable audit trails.