Archetypal / Archetypal Research
Research. Evaluation. Transition.
Archetypal Research
Advance frontier-model benchmarking, machine-readable policy, human–AI oversight, and secure deployment through Archetypal’s cooperative research program.
Frontier-model evaluation
Study what a model can establish under a defined set of conditions. Preserve scenario design, configuration, results, and unresolved questions so that findings can be examined independently.
Policy application
Investigate how institutional policy becomes a testable operational rule. Compare rule interpretations, boundary cases, and the effect of missing context on an enforcement decision.
Human–AI decision-making
Examine what information a reviewer needs to rely appropriately on an AI recommendation. Study review granularity, escalation, uncertainty presentation, and the practical burden of oversight.
Secure deployment
Connect evaluation findings to the operating environment. Define permissions, data boundaries, local behavior, change control, and the evidence needed for an authorized deployment decision.
Evidence and transition
Carry supported findings into the next experiment or implementation step. Keep experimental results separate from product commitments, independent validation, and authorization to operate.
Resources & collaboration
Research that can be examined.
Explore the CRADA research direction and the role of repeatable evaluation in moving from a model demonstration to an accountable workflow.