OpenAI's generally available Decisions API supports predefined choices, probabilities, and scores. Support routing is a natural candidate because the business often needs one of a small number of destinations rather than a generated explanation.
Define the labels carefully
Use queues that have clear operational meaning. Include a route for ambiguous cases and requests containing multiple issues. If a label cannot be applied consistently by trained staff, an AI classifier will not solve the underlying taxonomy problem.
Keep policy rules outside the prediction. A message suggesting urgency should not automatically override authentication or expose a restricted support channel.
Create a representative evaluation set
Sample across languages, customer tiers, incomplete messages, and rare but important cases. Keep sensitive data handling consistent with your approved contract and retention settings.
Measure the cost of each mistake, not just overall accuracy. Misrouting an ordinary question may add a delay; misrouting a critical service outage may be much more consequential.
Use confidence cautiously
The API's probability-related outputs can help set review thresholds, but their calibration should be checked on your own workload. A high reported probability is not proof.
Begin in shadow mode, comparing suggested routes with human decisions without changing the queue. Then enable only the categories that meet your acceptance criteria. Monitor reversals and escalation delays after launch.
The benefit comes from a faster, more reliable support process. That requires queue ownership and feedback, not merely adding an AI call before an existing routing rule.
Sources & further reading
Reviewed October 26, 2026. Product availability and regulatory guidance can change. Vendor performance claims are not independent Rovio AI benchmarks.
Found this useful? Share it.