How to take AI from demo to real-world deployment

▤ Summary

The article explains why promising AI prototypes often stall before production and outlines practical steps to turn demos into reliable, compliant systems. It draws on Unicorne’s voice-AI triage project for Québec clinics to highlight key challenges around latency, cost per interaction, data residency, and traceability. The team prioritized infrastructure-first design, running the pipeline inside AWS (Connect, Nova Sonic, Bedrock) to keep audio and logs secure and auditable. The piece stresses designing for handoffs to humans, managing model costs and latency, and asking unglamorous operational questions early to achieve real-world adoption.

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