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ExplainerAI™

Secure, Responsible and Explainable AI starts here.

Performance monitoring, explainability and transparency with guardrails for every AI model in your health system - Gen AI, ML and "blackbox" vendor models alike. Built inside leading academic health systems. Validated in production clinical environments.

One Platform to Govern Healthcare AI

Always deployed within your environment, ExplainerAI™ uses patented technology to tap directly into AI inferencing across both internally developed and third-party models to continuously assess performance, safety, and compliance.

You can read more about how ExplainerAI™ works under the hood.

Integrated with Epic and leading EHRs, ExplainerAI™ provides full model transparency into AI decision-making. It allows healthcare organizations to ensure that AI tools are compliant, ethical, trusted and optimized for real-world care delivery.

ExAI model analytics

- Key Features -

Hallucinations: "Judge & Jury" LLM ensemble detects Gen AI hallucinations. Runs responsible AI safety checks in real time.

Drift: Identify when inputs diverge from training data, flagging performance issues before they reach clinical workflows.

A suite of expanability dashboards monitor performance and surface issues such as hallucinations, drift, bias, fairness, PHI leakage and variables driving each model’s outputs. Informaticists, data scientists and clinicians see exactly what the model is doing and why.

 

15+ years of Epic integration expertise within health systems. 3x faster EHR integrations with AutoETL agent. Predictions, scores, and alerts are delivered directly within clinician workflows. Embedded Epic integration means no context switching for care teams.

 

On Prem or Private Cloud deployments - data never leaves your environment.

$100M+ in R&D investment, 15+ years of development inside leading academic health systems. 8 patents issued.

Centralized alerting across all models. Define model-specific thresholds and receive alerts before AI-driven risks cause harm. Comprehensive alerting configuration with full activity logs for auditors.

Granular security and privacy controls ensure compliance with HIPAA and NIST standards: detects models "leaking" PHI, role-based access controls, auditing including access tracking, lineage, traceability.

- ExplainerAI™ In Action -

Want to see how ExplainerAI™ delivers AI transparency?

- Where it Fits -

Operationalize Governance and Manage Risk Across the AI Lifecycle

Test the accuracy and performance of vendor models before committing to a purchase. ExplainerAI™ gives your team objective, evidence-based procurement criteria.

Leverage ExplainerAI™ while validating, training, and optimizing AI solutions. Identify bias and failure modes before models ever touch a patient record.

Ongoing monitoring and management of every live AI solution in your health system. Patented sensors tap into black-box vendor models without requiring source access.

Combined with our AI Discovery solution, AI Sniffer, Cognome's platform provides end-to-end AI risk management because you can't govern what you don't know.

Pre-Procurement | AI Sandbox | Validation | Training | Production | Optimization

Deployed at leading Health Systems

Read how leading health systems use ExplainerAITM

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- Real-World Use Cases -

  • Critical care

    Sepsis ML predictor

    Used for a predictive ML model, the Emergency Department’s care team views ExplainerAI™’s clinical explainability and ethical use dashboards to understand how and why the model made its prediction including all contributing factors.

  • Radiology

    Radiology Gen AI model

    ExplainerAI™ evaluates the outcomes from the model to ensure it has not hallucinated, providing clinical teams with the confidence to act on AI-generated radiology insights.

  • Oncology

    Spinal cancer predictor

    A nurse practitioner gets an alert if a predictive spinal cancer model exceeds thresholds set in ExplainerAI™, enabling timely follow-up with the appropriate care team.

  • Preoperative

    ASA scoring

    Operative teams view results of the model to assess accuracy of the model and whether it is exhibiting drift, ensuring ASA scoring remains reliable and clinically trustworthy over time.

     

Want to see how ExplainerAI™ integrates with your EHR system?

- Who it Serves -

Built for Healthcare AI Stakeholders
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IT, Security and Compliance

ExplainerAI™ equips technology, security, and compliance teams with the controls needed to accelerate AI adoption without exposing the enterprise to unmanaged risk.

Built on the NIST AI RMF delivering multi-layered risk detection, centralized alerting, agentic data mapping to Epic. HIPAA, NIST and Joint Commission level auditing.

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Informatics and Data Science

Observability, transparency and performance monitoring for any AI or ML model. Monitor models for drift, hallucinations, PHI leakage and other forms of degradation.

Pre-built analytics and dashboards aligned with NIH's framework for Responsible AI provide transparency, explainability, comparability and complete model details.

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Clinicians

Foster adoption through transparency with actionable insights. Clinicians trust AI when they can understand it to ensure proper care is being delivered at the proper time.

ExplainerAI™ surfaces the variables driving a model's recommendation, analysis or prediction. Turn "black-box" outputs into decisions clinical teams can act on confidently.

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Designed on leading frameworks for the Responsible, Secure and Compliant use of AI
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Cognome and our Partners are committed to accelerating healthcare transformation through the use of high performing, secure and Responsible AI solutions

Interested in partnering? Lets talk

Read about AI Governance and Risk Management

The $10 Million Risk: Securing Healthcare Enterprise Value Against Ungoverned AI (May 2026)

The new Standard for AI Certification in Healthcare (April 2026)

Request a Demo or Discovery Call