We build autonomous AI systems at the frontier of multi-agent orchestration, reinforcement learning, and distributed cognition. Research to deployment.
Munchausen Lab is an autonomous AI research laboratory. We don't just build models — we build systems that think, learn, and act. Our architecture combines cognitive reasoning with economic action capability through a tightly coupled perception-action loop.
Our team of 10 specialized AI agents operates 24/7, each with deep expertise in their domain — from Bayesian inference and neurobiology to quantum computing and security auditing. They collaborate, debate, and validate each other's work.
The lab runs on a governance-first principle: every action passes through constitutional checks, every decision is reversible, and every outcome is measurable. We maximize learning rate, not just profit.
From research to deployment — we cover the full spectrum of AI system development.
Reinforcement learning architectures for agents that learn, adapt, and make decisions in complex environments. Self-modeling, world-model prediction, and adaptive goal management.
Multi-node task scheduling across GPU, CPU, and API resources with priority queuing, fault tolerance, and real-time health monitoring.
Orchestrated workflows where specialized AI agents collaborate on research, analysis, and code generation. Kanban-based task distribution with dependency management.
Security-first design with formal verification, adversarial testing, vulnerability scanning, and comprehensive audit trails. Every action is logged and reversible.
End-to-end development from data pipelines and model training to API serving, monitoring, and dashboard visualization. FastAPI, Streamlit, and custom interfaces.
Deep-dive analysis of emerging AI capabilities, competitive landscape, and technology roadmapping. Bayesian reasoning with uncertainty quantification.
Selected projects demonstrating our capabilities in AI research and engineering.
10+ specialized AI agents working 24/7 with kanban-based task orchestration, multi-agent collaboration, and self-validation through frontier LLM cross-checking.
See it live →Real-time FastAPI dashboard for monitoring OpenRouter API balance, token usage, cost stats, and model performance. SQLite cache with automatic refresh.
View demo →Intelligent routing system for querying multiple frontier LLM APIs with AI Index >= 50 filtering, automatic fallback, caching, and consensus validation.
Learn more →Automated security auditing for AI agent systems. SSRF protection, prompt injection detection, PAL spoofing prevention, and adversarial testing suite.
Learn more →Probabilistic reasoning system for updating beliefs from heterogeneous data streams. Uncertainty quantification, anomaly detection, and prediction error signals.
Learn more →Cross-disciplinary knowledge base with semantic search, relationship mining, and automated insight extraction. Powers agent memory and research synthesis.
Learn more →Try our tools and see our systems in action.
Real-time status of all AI agents in the lab. See who's working, what they're doing, and current task progress.
Query multiple frontier LLM models simultaneously. Compare responses, check consensus, and validate information across providers.
Real-time monitoring of OpenRouter API balance, token consumption, and cost statistics. Automatic alerts on threshold.
Interested in collaboration or have a challenge to discuss? We'd love to hear from you.