Three ways to work together

AI Feasibility Sprint

For teams with an AI idea and an open question: can we build this, should we, and what will it cost to run?

• >An assessment of your data and use case
• >A recommended approach: a large language model, a classic model, or no ML at all
• >An architecture sketch and a running-cost estimate
• >A clear go or no-go, in writing

Production Review

For teams with a model or GenAI feature that is slow, fragile, expensive, or hard to redeploy.

• >A review of the code, data pipeline, infrastructure and evaluation
• >A prioritized list of fixes, each with an effort estimate
• >A walkthrough with your team

Fractional ML Lead

For teams that need senior ML judgment every week, but not a full-time hire.

• >Ownership of your ML roadmap and technical decisions
• >Code and model reviews
• >Deployment, monitoring and MLOps set up properly