AI engineering
AI features with evaluation and review paths.
We use models where they improve a task, connect them to the systems and data they need, and design for quality, security, cost, and human review.
Start with the task, not the model.
Document intake, knowledge search, classification, assistant interfaces, and workflow automation can be good candidates. Some are better solved with ordinary software. The choice depends on the data, the cost of mistakes, and who needs to review the result.
- 01
Frame
Define task, data, risk, review needs, and fallback behavior.
- 02
Prototype
Test models, retrieval, prompts, integrations, and UX quickly.
- 03
Evaluate
Measure quality against examples and failure cases.
- 04
Operate
Monitor usage, costs, quality drift, security, and feedback.
Have something to build?
Tell us what you are working on, what is getting in the way, and what needs to happen next. We can start there.