Notable vs Epic AI

Detailed side-by-side comparison to help you choose the right tool

Notable

Healthcare

Notable is an intelligent automation platform for healthcare that deploys AI-powered agents to streamline patient access, revenue cycle management, and clinical workflows. Used by health systems and physician groups, Notable automates tasks such as patient intake, prior authorization, registration, scheduling, and referral management—reducing manual work, accelerating reimbursement, and improving patient experience across the care journey.

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Starting Price

Custom

Epic AI

Healthcare

AI capabilities integrated throughout Epic's healthcare software platform, featuring AI charting, generative AI for EHR, and agentic AI to reduce documentation time and improve patient care workflows.

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Starting Price

Custom

Feature Comparison

Scroll horizontally to compare details.

FeatureNotableEpic AI
CategoryHealthcareHealthcare
Pricing Plans10 tiers10 tiers
Starting Price
Key Features
  • • AI-Powered Patient Intake
  • • Prior Authorization Automation
  • • Revenue Cycle Automation

    Notable - Pros & Cons

    Pros

    • âś“Purpose-built for healthcare with deep EHR integrations (Epic, Cerner, athenahealth) rather than adapted from generic RPA
    • âś“Covers the full patient journey from intake through revenue cycle and clinical follow-up in a single platform
    • âś“Pre-built workflow templates enable faster deployment (weeks, not months) compared to custom automation builds
    • âś“Reported up to 85% reduction in patient intake time and measurable improvements in revenue capture
    • âś“HIPAA-compliant and SOC 2 Type II certified, meeting healthcare data security requirements
    • âś“Patient-facing digital experience improves satisfaction and reduces no-show rates

    Cons

    • âś—Enterprise-only pricing with no self-serve tier makes it inaccessible for small independent practices
    • âś—No publicly listed pricing, requiring sales engagement to evaluate cost
    • âś—Depth of integration and customization may vary by EHR platform—strongest with Epic
    • âś—AI-driven automation in clinical workflows requires careful validation to avoid errors in patient-facing processes
    • âś—Organizations with heavily customized EHR configurations may face longer onboarding timelines
    • âś—Limited publicly available third-party reviews compared to more established RCM vendors

    Epic AI - Pros & Cons

    Pros

    • âś“Deeply integrated into the Epic EHR workflow, eliminating the need for separate AI tools or context switching during clinical encounters
    • âś“HIPAA-compliant AI pipeline with enterprise-grade security and privacy controls built for healthcare-specific regulatory requirements
    • âś“Access to Cosmos, one of the largest de-identified clinical datasets globally, enabling AI models trained on real-world healthcare data at massive scale
    • âś“Open-source AI validation framework allows health systems to independently verify and benchmark AI model performance before clinical deployment
    • âś“Broad scope of AI applications spanning clinical documentation, patient communication, medical coding, operational workflows, and agentic pre-visit automation
    • âś“Backed by Epic's installed base covering over 50% of U.S. hospital beds, ensuring rapid iteration informed by diverse real-world usage

    Cons

    • âś—Only available to existing Epic customers—organizations on competing EHR platforms like Cerner (Oracle Health) or MEDITECH cannot use Epic AI independently
    • âś—Pricing is opaque and negotiated per enterprise contract with no published rate cards; total EHR platform costs typically range from $50M–$500M+ depending on system size, making cost comparison or budgeting difficult without direct engagement with Epic sales
    • âś—Heavy dependency on Epic's proprietary ecosystem creates vendor lock-in; AI features cannot be decoupled or used with other EHR systems
    • âś—Implementation and customization require coordination with Epic representatives, which can be slow and resource-intensive for health systems
    • âś—Clinician trust and adoption varies—AI-generated notes and responses still require human review, and some providers report alert fatigue or skepticism toward AI outputs

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