AI Systems
& Data Infrastructure

Most organizations sit on large amounts of messy data. Contracts, registries, marketplace listings, internal documents – valuable information that usually lives in spreadsheets, PDFs, and manual workflows.

I build systems that turn this into structured intelligence.

That means automated pipelines, AI-assisted extraction, and applications that allow people to explore and analyze data that was previously unsearchable.

In practice, the interesting part is never the model itself. The challenge is building the surrounding system – the pipelines – the validation layers – and the interfaces that make AI useful in real workflows.

Much of my current work explores hybrid AI architectures, where local models and cloud inference operate together inside reliable data infrastructure.