Agentic systems, built for production

Design systems that can survive changing prompts, inconsistent source data, model churn, and the operational reality of running AI inside a business process.

What I architect

Semantic layers, retrieval systems, evaluation loops, guardrails, agent workflows, and the interfaces that let teams use them safely.

No vendor lock-in

Build around clear interfaces, replaceable components, and explicit observability so the system stays yours even when vendors or models change.

Related solutions

This bucket covers semantic layers, AI agents, RAG, workflow automation, and related technical pillars.

Selected work

Case studies should prove architectural judgment, production hardening, and the ability to connect AI to real operational outcomes.

Talk to me about your system

Use this page when the challenge is building the actual AI-backed system correctly.

Talk to me about your system