What this is
Retrieval systems over your own documents, classification and extraction pipelines, forecasting, and assistants embedded in workflows your team already uses.
We will tell you when AI is the wrong tool
A meaningful share of the AI projects we are asked about are better solved by a database query, a rules engine, or fixing a broken process. Hearing that early is cheaper than hearing it after two quarters of spend, so we say it in the feasibility phase.
Evaluation before deployment
No model reaches production without an evaluation set and a measured baseline. "It looked good in testing" is not a launch criterion. Where errors carry real cost — money, health, legal exposure — we design the human review step as part of the system, not as an afterthought.