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Enterprise Layer Intelligence
Categories/Healthcare & Life Sciences/ALIGNMT AI
ALIGNMT AI

ALIGNMT AI

Founded 2023

Track compliance standards and monitor real-world risks across healthcare artificial intelligence deployments

Pricing model

Demo

You can use ALIGNMT AI to monitor and audit artificial intelligence systems deployed across healthcare organizations. It tracks over thirty distinct risk factors, safeguards patient data, and identifies potential biases in training datasets. You can generate transparent report cards to show compliance with ONC HTI-1, ISO, and NIST regulatory standards to boards, regulators, and clinical stakeholders. The system also lets you evaluate third-party vendor models against de-identified real-world clinical benchmarks, ensuring your medical technology remains safe, dependable, and fully documented.

What ALIGNMT AI does

Audit training datasets to identify sources of bias and blind spotsMonitor live clinical algorithms for behavioral drift and safety risksGenerate compliance reports aligned with ONC HTI-1 requirementsBenchmark third-party healthcare models against real-world clinical datasetsCreate transparency report cards for regulatory audits and executive reviewTrack risk controls across organizational data, staff, and model deploymentsContinuous real-world tracking of over thirty risk factorsAutomated compliance alignment with ONC HTI-1, ISO, and NIST standardsPublic and internal transparency report cardsBias identification and blind spot detection across training datasetsThird-party vendor benchmarking with de-identified real-world clinical dataEnd-to-end audit trail generation for regulatory bodies and hospital boards

Pricing breakdown

Pricing model: Book a demo

Frequently asked

Electronic Health Records (EHR) APIs, FHIR Data Standards, AWS HealthLake, Google Cloud Healthcare API, Azure Health Data Services, Python SDK

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ALIGNMT AI, Trust Intelligence, AI governance, healthcare compliance, ONC HTI-1, NIST AI RMF, ISO AI standards, bias detection, algorithmic auditing, healthcare risk monitoring, AI report cards, vendor benchmarking, clinical AI safety, responsible AI, AI audit trails