Before a rule or model change goes live, it is run against a library of realistic scenarios. Regressions are caught in the lab, not in the waiting room.
Research
Evaluation & Safety Lab
Continuous testing of agents against practice-specific scenarios before and after every change.
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Digital Twin Studio
Consent-first creation of staff voice and likeness twins, with approval workflows and visible AI disclosure.
Learn moreZero-Retention AI Architecture
Generative AI calls run with customer-data opt-out and zero-data-retention settings. PHI is never used to train public or commercial foundation models.
Learn moreConductor Orchestration Engine
A multi-agent orchestrator that routes work, applies policy and keeps a single auditable record of every interaction.
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