The infrastructure layer for
local AI.
oQueo builds the infrastructure layer between local AI runtimes and real workflows - portable, self-managed, independent of any single cloud provider.
A platform built around real constraints
Not another cloud-dependent AI wrapper. Infrastructure that runs where you run it.
Autonomous agents designed for specific workflows. Each agent is self-contained, configurable, and runs against your local AI runtime.
A plugin slot architecture allows new capabilities to be added without touching core infrastructure.
DSGVO-compliant hosting on dedicated D-A-CH servers, deployment pipelines, and CDN - all managed, all controlled.
Twelve agents. Six live.
Six deployed and active, two in active development, four in the queue.
The real stack
Nine systems. Each chosen deliberately.
Dedicated servers in the D-A-CH region. Server hosting and storage stay in the EU. Further cloud services run in EU regions or under signed DPAs.
Postgres-based BaaS for structured data and authentication. Open source, self-hostable, production-grade.
Every deployment flows through GitHub Actions. Source of truth for code, config, and pipelines. GDPR-compliant via DPA.
Lightweight backend hosting for FastAPI services in EU region Frankfurt. Deploys directly from GitHub on push.
Handles DNS, proxying, and the Cloudflare Tunnel for local AI runtimes without opening ports. Global CDN - GDPR-compliant via DPA.
Serverless Redis in EU region (Frankfurt) for caching, queues, and rate limiting. Pay-per-request, zero cold starts.
Claude API (Anthropic) and OpenAI API as configurable cloud AI providers alongside local runtimes. Provider-agnostic by design. GDPR-compliant via DPA.
Open-source API client for testing and documenting all internal and external API endpoints. Self-hosted.
External monitoring for all public endpoints. Alerts on any downtime before users notice.
Four operating principles
Every architectural decision follows these constraints - not aspirational goals, but operational requirements.
Every agent runs against a local AI runtime - Ollama, LocalAI, or LM Studio - via Cloudflare Tunnel. No cloud API keys required at runtime.
The entire stack runs on shared hosting and a small Render instance. No Kubernetes. No AWS. No mandatory cloud dependency.
Each component is a discrete unit. The plugin slot pattern means new capabilities compose without touching existing modules.
MCP (Model Context Protocol) is the target integration standard - connecting AI agents to real-world data and tools.