Architect AI systems
AI systems & agent development
Production-grade AI agents, RAG, and semantic layers need to be modular, observable, and realistic about what fails in production.
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.
- Encrypted AI Romance Story App Market-facing Product
- Marketing and Sales Operations Platform Equity Venture
- Personal Brand Content Copilot Market-facing Product
- Press Brief Marketplace Market-facing Product
- Bilingual Reflection App for Psychologists Market-facing Product
- Customer Support Escalation Prediction Internal Tool
- Enterprise AI Platform for a Pharmaceutical Company Internal Tool
- Green Tech Grant Application Builder Internal Tool
- Legal Document Search for Law Firms Market-facing Product
- European Grant Matching API Market-facing Product
Talk to me about your system
Use this page when the challenge is building the actual AI-backed system correctly.