Patient outcomes depend on decisions backed by accurate data. Your data is ready to work harder.

CAMS runs on Google Cloud Platform, which is HIPAA-eligible infrastructure, and Covasant signs a Business Associate Agreement as a standard part of the engagement. Patient data is handled under strict role-based access controls, with data residency options to meet local regulatory requirements. Every agent action touching clinical data is logged and auditable through the AI Agent Control Tower. We do not use patient data for model training.

Retrospective auditing reviews a sample of claims after the fact, typically catching healthcare FWA weeks or months after it has occurred. konaAI monitors 100% of billing codes, claims submissions, pharmacy transactions, and procurement approvals in real time, flagging upcoding, duplicate claims, ghost procedures, and out-of-policy spending as they occur. For healthcare payers and providers facing CMS, OIG, or RAC audit scrutiny, the difference is proactive detection during the billing cycle rather than reactive discovery after an audit notice arrives. The $8.3 billion lost annually to healthcare FWA in the US alone is largely a detection timing problem, not a compliance effort problem.

konaAI uses a multi-model detection approach that combines rule-based checks with anomaly detection and contextual reasoning. For healthcare specifically, it is configured with billing code relationships, payor contract terms, and clinical workflow patterns so that flagged items represent genuine anomalies rather than legitimate edge cases. During the initial deployment period, KonaAI is tuned against your specific billing patterns and payor mix. Typical false positive rates are reduced by over 60% compared to rule-based systems within the first eight weeks of deployment.

Yes. TPRM for healthcare monitors your full medical device, pharmaceutical, and health IT vendor ecosystem continuously for financial distress, quality certification lapses, cybersecurity vulnerabilities, regulatory sanctions, and recall risk. For healthcare organisations where a vendor failure is a patient safety event and not just a procurement problem, annual questionnaire-based vendor assessment is structurally inadequate. TPRM flags the signals that precede a recall or supply disruption early enough for your procurement and quality teams to act before patient care is affected. Vendor risk scores update daily rather than on the annual cycle that most healthcare supplier risk programmes still depend on.

For ready-built products like konaAI and TPRM, initial deployment in a healthcare environment typically takes six to ten weeks, depending on the complexity of your billing systems and vendor data landscape. Clinical AI products built on CAMS for specific use cases, such as clinical decision support or revenue cycle intelligence, have timelines of twelve to twenty-four weeks from problem definition to validated deployment. Our go-live definition means the product is running in your actual operational environment, not a sandbox demonstration.