King and Worthington compared 134 paid expert pre-reviews of 124 manuscripts with Claude Opus 4.8 reviews: the GPT-5.5 judge chose the AI review in all 132 decided pairs, and three former journal editors chose it in 26 of 30 judgments. The result covers constructive pre-submission feedback, not journal refereeing.
Evaluate in two layers: did retrieval find the source passage, and is the answer grounded in it and correct. Looking only at answers can fool you: one study found that when the context wasn't enough to answer, models still got 35% to 62% right using their own knowledge, which breaks on questions only your organization can answer. Use order 11's test questions for both layers, and evaluate permission-crossing and unanswerable questions too; calibrate LLM judges against human samples. After launch, turn escalated and complained-about conversations into failure cases, hand them back to document owners, and add them to the test set.
Braintrust connects versioned datasets, immutable experiments, scorers, and production traces into one evaluation loop. Its value is not another score but the ability to turn production failures into offline tests. The company announced an $80 million Series B in February 2026; its customer list is company-reported.