Start with volume, not novelty
The strongest early automation candidates are boring: invoice matching, document classification, support ticket triage, order exception handling. They are repetitive, well-defined, and happen hundreds of times a day.
Novelty use cases attract attention but rarely survive a cost review, because the work being replaced was never expensive in the first place.
- How many times per day does this workflow run?
- How long does one instance take a person?
- How consistent is the input format?
- What is the cost of an incorrect output?
Define the evaluation before you build
Agree a test set and an accuracy threshold up front. Without one, every discussion about whether the system is good enough becomes a matter of opinion, and projects stall in perpetual pilot.
Treat the evaluation set as a product asset. It is what allows you to change models or prompts later without guessing at the impact.
Design for the uncertain cases
The failure mode that damages trust is not a wrong answer — it is a wrong answer delivered confidently into a customer-facing process. Confidence thresholds and human review queues keep that from happening.
A system that handles 70% of volume automatically and routes the rest to a person is usually more valuable than one that attempts everything unreliably.
Written by Nexora Engineering. If you would like to discuss how this applies to your environment, we are happy to talk it through.
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