Errors and inconsistent answers can leave review and correction work unchanged. SYSLABO evaluates real questions against their source information and checks whether answers fit the case and relevant time period. We investigate why errors and inconsistencies occur and compare results on the same basis after document or model changes, so you can decide whether the AI can be used in your work.
We prepare real questions and expected answers or processing results. Evaluation covers correctness, evidence, the relevant case and time period, and how AI should respond when information is insufficient.
We analyze answers that staff corrected and examine their supporting information and the conditions under which it was used. We identify where improvements are needed, such as reviewing documents and data or reviewing the AI environment.
Compare using the same questions and data.
We compare results using representative questions and data after document or model changes. We document improvements and remaining issues so your team can decide whether to use the revised system.
We share the questions, data, expected results and methods used in evaluation. Combined with joint development and reviews of documents and data, we look for ways to reduce the effort of checking and correcting answers.
Tell us about the questions that did not get the answers you expected, the answers given and the parts your staff corrected. We set the evaluation criteria and the order for investigating causes, and move forward with the data or feature improvements needed.
You can contact us before your questions or documents are fully organized.
