Scientific curiosity. Engineering discipline.
Explore broadly, then narrow the system until its behavior can be explained, measured, and maintained.
I build the system around the model—context, memory, tools, evaluation loops, and safety boundaries. Capability matters when it becomes reliable behavior.
A small selection of systems built to make model behavior more useful, legible, and controlled.
A deterministic Python policy gate that turns agent tool calls into auditable allow, deny, or confirm decisions—before execution.
An end-to-end agent network: orchestrator, policy, research, and provider agents communicating across A2A and MCP.
A production-oriented retrieval API with FastAPI, PostgreSQL, pgvector, document pipelines, health checks, and cited answers.
A clinical language pipeline that combines specialist models, builds domain-ready training data, and adapts information extraction for medical text.
Reliable agentic software is interface design: what the model can see, what it can do, how its work is checked, and where people remain in control.
Explore broadly, then narrow the system until its behavior can be explained, measured, and maintained.
Useful ideas should leave the notebook. Open source turns personal learning into shared infrastructure.
Safety, privacy, and trust are not finishing layers. They shape the architecture from the first interface.
Open work across research, education, and production systems. Built to be studied, challenged, and improved together.
OPEN-SOURCE WORK ↗A focused technology studio turning AI systems into pragmatic, reliable production work.
VISIT COMPANY ↗