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Quickly unlock clinician productivity and increase satisfaction

A weeks-long program that sets a team of your clinicians up with an AI tool that effortlessly reads long patient charts and other clinical context then surfaces the relevant information, fully cited, in exactly the format they need

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MedWatch achieved a 3x clinician productivity in UM, CM and PI workflows, with 92% satisfaction rate and 97% clinical accuracy.

Capabilities rolled out alongside your clinicians in a week, not to them in a year

Adjust templates alongside our forward deployed clinicians so they fit your workflows, not the other way around.

Flow unlocks clinician capacity across specialties

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Utilization Management

Evidence ready at the point of review

Surface guideline-aware clinical evidence at review, fully cited — so UR decides faster with less chart digging.

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Care Management

Spend more time on the care plan

Pull history, risks and care gaps into one cited summary, so care managers start the call already informed.

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Disease Management

Spot deterioration earlier

Flag members whose chronic conditions are drifting across years of notes, so outreach happens before they escalate.

Powered by Florence

Capable, trustworthy and integrated AI

Florence is our AI system designed specifically for performing highly regulated and complex work in health plan environments.

Capable

  • Proven across the breadth of plan workflows

    Built on frontier models that can reason and work across modalities — charts, faxes, structured feeds, and policy text — so Florence handles clinical and administrative work across utilization management, case management, HEDIS, risk adjustment, and payment integrity.

  • Captures organizational knowledge

    Florence encodes how your plan actually decides: tacit knowledge, accepted evidence, and organizational interpretations of policy and thresholds. Those standards stay version-controlled and reusable, so every workflow reflects the way your organization works.

  • Evaluation and feedback built in

    Synthetic data and large-scale evaluation catch issues before deploy. In production, feedback from LLM checks and human review flows back into the system so Florence keeps improving with every case.

trustworthy

  • Complete traceability of reasoning

    Each outcome includes the reasoning and supporting evidence behind it — relevant record findings and the specific policy criteria applied — so any result can be reviewed and substantiated on demand.

  • Immutable decision ledger

    Every action, from record access through final outcome, is written to an immutable ledger of events. That record keeps all activity auditable for appeals, regulatory review, and internal quality assurance.

  • Compliant by construction

    Built to HIPAA, SOC 2, NCQA/URAC, and applicable federal and state AI and interoperability requirements. Work completes automatically only where criteria are clearly met; otherwise Florence escalates to a qualified human with a sourced evidence packet.

integrated

  • Ingests data in its existing form

    Florence uses FHIR internally and normalises inbound data on ingestion, so plans keep current formats and channels. Supported inputs include X12 EDI, HL7 v2, C-CDA, NCPDP, SFTP extracts, proprietary feeds, and unstructured PDFs, faxes, and scans.

  • Standard and bespoke integration paths

    Documented SDKs and APIs expose Anterior's production capabilities directly for common plan systems, with clear contracts for production traffic. Bespoke integration remains available wherever a plan's architecture requires a custom path.

  • Flexible deployment

    Interface components can run standalone or embedded in existing plan systems. Florence operates as autonomous background agents or under human-in-the-loop review, fitting the plan's operating model rather than reshaping it.