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AI ARCHITECTURE

How is Burna AI's grading engine built?

As twelve specialized agents in a cascading constraint pipeline. Each agent does one narrow job, and its output bounds what every agent after it may conclude, so a later step cannot produce a grade that contradicts an earlier finding. The twelve cover extraction, verification, resolution, standardization, taxonomic matching, differential analysis, temporal tracking, documentation integrity, evidence synthesis, causal attribution, confidence calibration and regulatory encoding. Output is constrained to valid CTCAE terms and grades for the trial's version, and every grade carries its source sentence and the CTCAE criterion it meets. That is what citation-bound means here: the basis for each suggestion is attached, so a clinician can check it independently. Two patents have been filed on the architecture, and a qualified investigator reviews and signs every grade.

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