Separate functions examine the same hypothesis from different positions.
Separate functions examine the same hypothesis from different positions.
Dissent-first by design
Traditional AI systems optimize for consensus. Quvant optimizes for documented disagreement: when models diverge, the system records the dissent rather than hiding it. This produces artifacts that withstand auditor scrutiny because they disclose their own limits.
Four roles, four architectural families
Analyst
Generates hypotheses and maps regulatory coverage from the source evidence.
Critic
Searches for exceptions, gaps, and edge cases that undermine the Analyst's conclusions.
Synthesizer
Integrates the Analyst and Critic perspectives, prioritizes findings, flags residual gaps.
Validator
Blind terminal validation: receives only the original input and the Synthesizer verdict, verifies without access to the debate.
See the architecture section above for the four deliberative roles.
Why the Validator is blind
The Validator never sees the intermediate debate. It receives only the original input and the Synthesizer's final verdict. This prevents anchoring bias: the Validator evaluates the conclusion on its own merits, not on the persuasiveness of the debate that produced it.
Automatic HALT below threshold
When confidence drops below the calibrated threshold, the system stops and documents why — no indefensible output is produced. The HALT state is a feature, not a failure: it means the system recognized the limits of the available evidence.
Models are updated automatically. We do not publish specific versions. The architecture (roles, blind validation, HALT behavior) is stable; the specific models that fill each role evolve as better options become available.
See the methodology in action
Inspect the Evidence Pack it produces — including the Dissent Record and confidence score.