I build AI products and help people put them to work.

Our team has built and deployed software for PE customers that analyzes tens of thousands of financial and legal documents across a data room, finds inconsistencies and flags deal risks with supporting sources.

In our synthetic data-room benchmark, AI using Colabra scored up to 31% higher on output quality than the same AI using a leading data room's public document-retrieval tools. The comparison and what we tested.

Colabra began as software for scientific research. Today, customers can also use the data ingestion tools behind it in their own AI systems. I think many people have yet to see how much AI could help in their work, even as the models become more capable. I want Colabra to help them use those capabilities, get time back, and take on work that used to feel out of reach.

I studied chemical and biological engineering at Princeton, co-authored battery research in Energy & Environmental Science, and served as technical lead on an ARPA-E-funded project at 24M Technologies.

I taught myself machine learning at night before building my first company. I later worked on commercially deployed models in regulated consumer lending, where we had to meet compliance requirements and explain credit decisions.

Journey connects those chapters. About has my research, running, piano, and contact details.