A fluent answer is not a correct one, and only your specialists can tell the difference. In Kili they evaluate LLM outputs, write and correct the examples your model is post-trained on, and annotate the text behind it, while Kili measures how far they agree.
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The specialists who can tell a correct answer from a plausible one do the judging themselves. Model outputs, contracts or clinical notes load as text or PDF assets, and your experts grade each against your criteria, mark named entities and relations, and correct the model's pre-annotations, without writing any code.
Every expert judgment can become post-training data. In Kili's experimental LLM projects, specialists prompt two or more models, rank their responses, rate single turns and whole conversations, and write a better answer when none is good enough. Conversations traced from production can be imported and judged the same way.
Quality stays measurable, and the text stays where it must. Consensus scores how far experts agree on each class or entity, Honeypot checks them against answers you trust, and a second reviewer signs off. Files can stay in your own cloud bucket while you use Kili's cloud, or Kili runs on your own Kubernetes.
Speak to our team for a free 14-day evaluation.
Kili Technology is a complete data suite that supports all data types and handles specialized formats for domain-specific requirements.
Customer stories from the programs that put this to work — with the numbers behind them.
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Got questions about Kili Technology? Check out our FAQ. If you can't find it in this list, drop a question for our team.
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