Regard vs Glass AI

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

Regard

🟢No Code

Document Management

AI clinical insights platform that reviews 100% of patient chart data to recommend diagnoses, generate draft documentation, and surface missed conditions at the point of care.

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Starting Price

Paid

Glass AI

🟡Low Code

AI Development Assistants

Clinical decision support AI that assists healthcare professionals with differential diagnosis, medical knowledge search, and evidence-based clinical reasoning.

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Starting Price

Freemium

Feature Comparison

Scroll horizontally to compare details.

FeatureRegardGlass AI
CategoryDocument ManagementAI Development Assistants
Pricing Plans50 tiers8 tiers
Starting PricePaidFreemium
Key Features
  • Health monitoring
  • Symptom analysis
  • Treatment recommendations
  • Ambient AI scribing
  • Differential diagnosis generation
  • Clinical decision support

💡 Our Take

Choose Glass AI if you want a clinician-driven workflow where you author the problem representation and Glass returns differentials and notes you control. Choose Regard AI if you are a hospital IT team looking for an EHR-integrated platform that proactively scans patient charts to surface missed diagnoses across an inpatient census — Regard is institution-deployed; Glass is clinician-deployed.

Regard - Pros & Cons

Pros

  • Reviews 100% of patient chart data — catches conditions that clinicians miss when manually reviewing the 3% they have time for
  • Generates draft clinical documentation before the physician encounter, saving 10+ minutes per note
  • Proven revenue impact: Sentara Health saw 17% increase in CC/MCC capture with 4x ROI per user
  • Integrates directly into Epic and Cerner workflows — no context-switching to a separate application
  • Reduces CDI query burden by proactively documenting diagnoses, saving CDI teams ~60 minutes per avoided query
  • Combines ambient conversation data with chart data for more complete clinical picture
  • HIPAA-compliant with enterprise-grade security appropriate for hospital environments

Cons

  • Enterprise-only pricing with no self-service tier — requires a sales process and implementation timeline
  • Currently focused on hospital medicine (hospitalists/internists) — limited applicability for outpatient or specialty practices
  • Implementation requires EHR integration work that can take weeks to months depending on the health system's IT infrastructure
  • Physician adoption depends on trust in AI-generated suggestions — some clinicians may resist AI-recommended diagnoses

Glass AI - Pros & Cons

Pros

  • Bundles ambient scribing and clinical decision support in one subscription, replacing what would otherwise require two separate tools (typically $150-$400/month combined)
  • Pro tier at $90/month is competitive against standalone AI scribe products and includes unlimited usage of both scribing and decision support
  • Available on iOS, Android, and web, letting clinicians capture encounters on a phone in the exam room and review notes from a desktop later
  • Evidence-based diagnostic suggestions are grounded in current medical literature, helping clinicians consider comprehensive differentials for atypical or complex presentations
  • Educational value for medical residents and students — the structured problem-representation-to-differential workflow mirrors how clinical reasoning is formally taught
  • Max tier ($200/month) adds direct EHR integration so AI-generated notes flow into the chart without copy-paste

Cons

  • Restricted to licensed healthcare professionals — patients and non-clinical users cannot access the platform for self-diagnosis or general health questions
  • Specialty depth varies: well-suited to general internal medicine, family medicine, and emergency medicine, but may underperform on rare diseases or narrow subspecialties (e.g., advanced oncology subtypes, rare genetic disorders)
  • EHR integration is gated behind the $200/month Max tier — Pro users must still copy notes manually into their charting system
  • Output quality is bounded by the quality of clinician input: incomplete histories or vague problem representations produce weaker differentials
  • HIPAA and institutional compliance review is typically required before clinics can deploy ambient scribing on real patient encounters, adding rollout friction

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🔒 Security & Compliance Comparison

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Security FeatureRegardGlass AI
SOC2✅ Yes
GDPR✅ Yes
HIPAA
SSO✅ Yes
Self-Hosted❌ No
On-Prem❌ No
RBAC✅ Yes
Audit Log✅ Yes
Open Source❌ No
API Key Auth✅ Yes
Encryption at Rest✅ Yes
Encryption in Transit✅ Yes
Data Residency
Data Retention
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