Zero hallucination format.

The problem isn’t the model. The problem lies in three distinct structural issues. First is, how concretely is the data structured. Second, where exactly did the data come from. And third – making sure the AI response is correct. AI output has no floor. Without one, output is probabilistic. Likely correct, but structurally unverifiable. Tasset’s zero hallucination format (ADAP) does not prevent an AI from hallucinating. It makes the knowledge source addressable and verifiable.

Tasset structures information by assigning a deterministic, uniquely identifiable agentic data address protocol (ADAP) immutably anchored to every line and cell of information in a file. Every anchor stores the ground-truth data at its ADAP coordinate and can be clicked and traced back by humans to verify its context and source.

To ensure every bit of information is cited correctly, Tasset’s ADAP carries its own verification layer that programmatically checks each data value by string comparison. An AI response grounded in ADAP anchors produces a deterministic citation checked and verified with a hallucination score. H = 0.0 means a citation has been source checked and verified. With ADAP, source knowledge citation use and accuracy does not depend on model, model quality or model version. Verification now becomes a deterministic property of the data format and structure, and not by inference or an AI’s confidence.