Trends & insights

You are listening to an AQPTech audio briefing: From AI pilots to everyday operations.

An AI project should begin with a decision to improve. Who will use the result? When do they need the information? What action follows? These questions turn a technology idea into a workflow that can be tested.

Evaluation data should represent the operating environment. For factory cameras, consider viewing angles, lighting, shifts and difficult cases. Keep tuning data separate from evaluation data. Agree how false alerts and missed events will be recorded.

Detection results are only part of the workflow. Test event delivery, permissions, retention and the way an operator verifies information. When something fails, the team needs to know where the data is and who owns resolution.

Start with a scope small enough to inspect and specific enough to support a real task. Evaluation evidence should guide whether to revise or expand. Follow the links below for the full article or to discuss your project context with AQPTech.