The gap between a demo that impresses and a system that runs 50,000 times a month without supervision is a matter of design, not scale.
AI for Operations · 8 min read · May 2026
The short version
Volume and edge cases. A demo handles the happy path once; production handles malformed inputs thousands of times, unattended, and has to fail safely every time.
Three things: a defined escalation path for uncertain cases, an immutable log of every action, and confidence thresholds that decide automatically when a human must step in.
Route by task. A classification step uses a small model; only the hard cases reach a frontier model. The cheapest reliable path that satisfies the compliance boundary wins.
In full
A proof-of-concept earns applause in a meeting. A production agent earns its keep running unattended, at volume, against inputs nobody anticipated.
We build on Azure AI Foundry with model routing chosen for cost and task, never novelty, and no regulated decision runs without a human in the loop. The discipline is the product.
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