What's the difference between a point AI tool and a healthcare AI platform?
A point AI tool does one isolated task — transcribe a visit, summarise a note, answer a chat — and stops there. A healthcare AI platform runs many such tasks on shared infrastructure: the same patient context, access controls, human-review checkpoints, and audit trail across every workflow. The practical difference is governance and reuse — a point tool leaves a hospital stitching together separate vendors and data flows, while a platform gives one governed environment where new use cases plug in without rebuilding the controls each time. AI writes. Doctors decide.
Point tools are easy to buy and easy to outgrow. Each one solves a slice — scribing, coding, intake — but the hospital inherits the integration, the duplicated patient data, and a different audit story for every vendor. When a regulator or a medical director asks 'who saw this data and who signed this output', the answer is scattered across five products.
A platform inverts that. Patient context, identity and access, the human-in-the-loop checkpoint, and the audit log live once, underneath, and every workflow draws on them. That is what makes governed healthcare AI durable: the governance is the architecture, not a feature each tool re-implements. Micromeet's products — MCU CoPilot, AI Scribe (Voice-to-EMR), Care Loop, Claim Readiness — run on that shared, governed layer rather than as disconnected apps, so adding a use case extends the platform instead of adding another silo.
Related questions
Can't we just buy several point tools and connect them later?+
Does a platform lock the workflow into one vendor's way of working?+
Micromeet — AI for governed healthcare. MCU CoPilot, AI Scribe (Voice-to-EMR), AI Front Desk, Care Loop, Claim Readiness and AI Care Command Center — every output doctor-reviewed. AI writes. Doctors decide. See the public benchmark →