I design and deploy local-first AI systems for enterprise environments.

On-prem LLM infrastructure. Data sovereignty. Audit-ready architectures built to meet modern regulatory standards.

Most AI systems fail at the control boundary.

Teams rush into APIs, leak sensitive data, and retrofit governance later. By the time risk is visible, it's already embedded in the system.

What I build

• Local RAG systems with deterministic routing (Mixture-of-Experts)
• On-prem LLM deployment (Ollama / llama.cpp / air-gapped)
• Data sovereignty architecture (no external dependency paths)
• Agentic workflows with enforced control boundaries
• Audit-ready systems aligned with “Reasonable Care” standards

Selected outcomes

• Reduced cloud AI costs by up to 90% via local-first architectures
• Deployed air-gapped inference systems for sensitive environments
• Built multi-agent reasoning systems backed by knowledge graphs
• Designed governance layers that evaluate intent before execution

Engagement

I work directly with a small number of teams on high-impact systems.

• 6-month contracts
• Enterprise environments only
• Focus: architecture, deployment, and control systems

If you are exploring AI, I am not the right fit.
If you are deploying it into critical workflows, we should talk.

Contact

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