Your model works. The problem is that people do not trust it, do not understand what it just did, or cannot correct it when it gets something wrong. That is a design problem, and it is the one that decides whether an AI product gets adopted or quietly abandoned after the demo. I designed the human-in-the-loop review system for a claims platform that cut processing time by 48% and human error by 64%, and the conversational onboarding at Learntech that took course completion from 31% to 64%. In both cases the win came from designing what happens when the AI is uncertain or wrong - not from the happy path.

• Audit of your current AI experience and where trust is breaking down

• Designed core AI flow including confidence, provenance and correction states

• Human-in-the-loop review model if your buyers need auditability

• Interactive Framer prototype, tested with real users before handoff

• Handoff spec covering failure, uncertainty and override behaviour

Teams whose model is not working yet - design cannot fix a bad model, and I will tell you that on the call rather than after invoicing you. Anyone who wants an AI-themed landing page rather than an AI product. Teams who want the interface to hide the fact that AI is involved.