Platform capability · Your experts in the correctness loop
Your experts shape what correct means.
Bring your experts’ reasoning, preferences, and exceptions into the standards your AI is developed against. Lemon Elicit prepares and adapts the work around their contributions, then develops findings into proposed rubrics, policies, and coverage for expert review.
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Ways to contribute
An accepted answer rarely contains the whole standard. Experts recognize exceptions, weigh competing objectives, and know when the evidence is insufficient. Their contribution can be a comparison, an annotated trajectory, or a conversation. Lemon Elicit prepares the context and follows the distinctions that need clarification, so participation develops knowledge the team can apply beyond that review.
Output curation
Ask an expert to assess, correct, or establish the appropriate output for a case. Curation helps uncover missing facts, domain requirements, and qualifications that a preference ranking alone may leave unresolved. Lemon Elicit prepares the material and develops the response into findings about acceptable behavior.
The correctness loop
Expert participation establishes the judgment that guides AI development. The resulting criteria and coverage also make it possible to identify precisely where further expertise is needed.
Experts compare outcomes, explain their reasoning, and identify the evidence or exception that changes a decision. Lemon Elicit adapts the next review or question around what remains unclear.
Lemon Elicit develops findings into proposed policies, rubrics, and coverage. Experts inspect whether the interpretation preserves their intent before it becomes an accepted standard.
Coverage guides Lemon Weave’s case construction and training material. Trialground applies the relevant rubrics to candidate behavior; Lemon Code and Goal support harness development against those expectations.
New usage, a conflict, or a trial result can expose an unresolved condition. Further contributions build on the reasoning already established, directing expert time toward what has changed or remains uncertain.
Participation and authority
Lemon prepares reviews, comparisons, and conversations around a learning objective. It interprets contributions and proposes follow-up work. Your experts contribute the judgment that the process is designed to uncover.
Output curation, pairwise and listwise comparisons, trajectory reviews, forms, chat, and voice reveal different aspects of expertise. A contribution can move from reviewing a concrete case to discussing the condition behind it.
Differences between judgments, including intra-expert inconsistencies, can reveal an unstated boundary or missing condition. Focused clarification helps teams distinguish a real policy conflict from a difference in context.
A contribution and an AI interpretation are distinct. Experts and accountable owners decide whether proposed rubrics and policies faithfully express the intended judgment. Teams can inspect the evidence behind those proposals.
How preparation, interpretation, and further expert work belong in the same development system.
Connected products and capabilities
Start from the work you have
Bring a development question and the experts who understand the work. We can identify a useful first contribution and how its findings should inform your benchmarks or development process.