How We Built an LLM Review Pipeline and Why 91.67% Accuracy Wasn’t Enough
Before this became a nightly product, competitor-review analysis started with a screenshot.
Someone would take the first visible page of public reviews, pass it to ChatGPT, and stretch the result with an estimate of monthly review volume. It was fast. It was also a little too convincing.
The number looked precise. The method was not.
Customer Care and the CRO wanted a simple thing: keep track of competitors. In practice, that meant answering a messier set of questions. Which companies? Which markets? How often? What labels? What would count as a real signal?
None of that was obvious at the start. We began with roughly five companies in two markets. The production workflow now covers fourteen companies, including our Company, across three markets. It runs every night and is still in use.
From one review at a time to a nightly workflow
The project did not start with fine-tuning. We...
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