AI Architecture and Prototyping for Product Teams

AI system architecture for product teamsMathijs Boezer designs and builds LLM, agent, and voice AI systems for real products.Lead AI Engineer at Trengo. Previously at Pandora Intelligence. MSc in AI, TU/e.What I Help With

Architecture Reviews - A focused deep dive into your AI system architecture, tradeoffs, and technical risks before scaling.

Prototype Sprints - Fast prototypes to validate AI product ideas, workflows, and feasibility before committing a full team.

AI Platform Design - Multi-tenant AI platforms, model routing, cost controls, evaluation, and observability.

Agent and Voice Systems - LLM workflows, tool use, orchestration, and real-time voice infrastructure for production.

AboutI studied Artificial Intelligence at Eindhoven University of Technology and have since worked across software engineering, machine learning systems, and production AI architecture.At Pandora Intelligence, I designed LLM-powered systems for complex regulatory and risk datasets. At Trengo, I work on AI agents and real-time voice systems for large-scale customer workflows.Independently, I work with a small number of product teams on AI architecture, prototyping, and implementation support.Latest InsightsWhy Voice AI Is Harder Than Chat AI - Voice AI sits at the extreme end of the latency spectrum. The pipeline, the UX, and the failure modes are fundamentally different from chat.Reducing Latency in LLM Systems: How We Got an Agent Pipeline Under 500ms - Most agent systems feel slow because they are architected to be slow. The model is rarely the bottleneck anymore, and measuring everything else is where the real gains are.Why AI Demos Fail in Production - The gap between a compelling demo and a reliable production system is where most AI projects die. The problems are predictable, and the fixes are systematic.