Find a practical first use case
Compare the value of the task with its data needs, error costs, and the effort needed to operate it.
I help founders and teams decide where AI is useful, how to build it, and how to test the result. That can mean an assistant for internal documents, a workflow agent, or an in-house model with controlled access.
Compare the value of the task with its data needs, error costs, and the effort needed to operate it.
Work through model choices, retrieval, tool access, human approvals, and cloud or in-house deployment.
Define representative examples, quality thresholds, cost assumptions, and the failures you need to catch.
Agree a small prototype or integration, its acceptance criteria, and what would still be needed for production.
Depending on the scope, you can leave with an architecture sketch, a model comparison, an evaluation plan, or a working pilot. For example, we could define the sources, permissions, and test questions for an internal document assistant before choosing a model.
See pricing or read how we work together. We agree on the output before paid work starts.
An in-house model can give you more control over deployment and data flows. Access controls, logging, operations, and compliance requirements still need their own design and review. A pilot does not by itself establish production readiness.
My work at AdPrompt covers AI pipelines and product architecture. My GasGuard research examines LLM-assisted vulnerability detection and repair. More about my background.
A conversation about your situation, the decision you need to make, and whether I can help.
Share a brief and bookFocused advice, a technical discussion, or a review. One-hour minimum, with preparation and limits agreed in advance.
Discuss hourly workFor an assessment, implementation, or ongoing support that needs its own scope and price.
Tell me about the projectShare a short brief first, then choose a time for a free 30-minute initial meeting. Paid work starts only after we agree the scope and price.
Tell me about the task, the people doing it, and what a useful result would look like.
Read the overview, or ask your preferred assistant.