Overview: What Is Regard?
Regard is a clinical AI platform built specifically for hospital medicine. Unlike ambient AI scribes that focus on capturing the physician-patient conversation and turning it into a note, Regard reads the EHR chart itself — labs, imaging reports, vitals, prior notes — and surfaces diagnostic suggestions, missed comorbidities, and documentation prompts that ensure conditions are accurately captured and coded. It is the only AI platform we cover that focuses primarily on diagnostic insight from existing EHR data rather than documentation generation from new conversations.
Founded in 2017 in Los Angeles, Regard has raised $81.9M including a $61M Series B led by Oak HC/FT. The platform is deployed at Sentara Health and other US health systems, and Regard recently announced an integration partnership with Microsoft Dragon Copilot showcased at HIMSS 2026. The Dragon Copilot integration is meaningful: it pairs the dominant ambient scribe (Nuance/Microsoft) with diagnostic AI from EHR data, giving physicians both a note generator and a diagnostic safety net in one workflow.
Key Features
- AI-powered clinical diagnosis suggestion from EHR data
- Automated clinical documentation drafting in physician's style
- Comorbidity and missed diagnosis detection
- EHR chart data analysis for diagnostic insights
- Integrated ambient scribe functionality
- Microsoft Dragon Copilot partnership integration
- Real-time clinical insights during care
- Revenue integrity through accurate diagnosis capture
The Differentiator: Diagnostic Insight, Not Just Documentation
Most AI in clinical workflows today is either ambient documentation (Abridge, Suki, Freed, Nuance DAX) or imaging triage (Viz.ai, Aidoc). Regard occupies a different lane: it reads structured and unstructured EHR data and asks "is there a diagnosis here that the physician hasn't yet documented?" The classic example is a hospitalized patient whose labs and vitals suggest acute kidney injury or sepsis criteria that have not been formally captured in the assessment. Regard surfaces those suggestions in real time, both improving care and ensuring revenue integrity through accurate coding.
This is a meaningful clinical and financial value proposition for hospitalists. Missed comorbidities are a significant source of underbilling and quality-metric problems, and they are exactly the kind of pattern that AI reading the chart can catch reliably.
FDA Status
Regard is not classified as a medical device. It likely falls under the 21st Century Cures Act non-device Clinical Decision Support criteria, which exempt CDS tools from FDA device regulation when they meet specific conditions including transparency about the basis for recommendations and the clinician's ability to independently review the reasoning. This is the standard regulatory posture for diagnostic CDS tools and is appropriate for Regard's use case.
Pricing
Regard uses opaque enterprise pricing with per-provider or per-facility licensing typical of clinical AI. Multi-year contracts are standard. The sales positioning emphasizes ROI through improved coding accuracy and revenue capture, which is a more concrete value lever than productivity claims and tends to land well with hospital CFOs.
Pros & Cons
Strengths
- ✓ Unique focus on diagnostic AI from EHR data
- ✓ Microsoft Dragon Copilot integration partnership
- ✓ Detects missed diagnoses and comorbidities
- ✓ Clear ROI through revenue integrity and coding accuracy
- ✓ Sentara Health and other production deployments
Weaknesses
- ✗ Smaller company — $81.9M total funding, still Series B stage
- ✗ Primarily hospital/inpatient focused — limited ambulatory use case
- ✗ Opaque enterprise pricing
- ✗ Narrower feature set compared to full EHR platforms
- ✗ Early stage of Dragon Copilot integration (showcased at HIMSS 2026)
- ✗ Limited public review data (no G2/KLAS scores found)
Who Should Evaluate Regard?
Regard is built for hospital medicine programs, hospitalist groups, and health systems focused on improving diagnostic accuracy and revenue integrity in inpatient settings. It is particularly well-suited to organizations already using or planning to deploy Microsoft Dragon Copilot, since the integration combines ambient documentation with diagnostic AI in a unified workflow. It is less relevant for ambulatory practices, where the underlying EHR data is typically less rich than inpatient charts.
Verdict
Regard occupies a clinically valuable niche that no ambient AI scribe directly addresses. For hospitalist programs and inpatient health systems concerned about missed diagnoses, comorbidity capture, and the revenue implications of incomplete coding, Regard belongs on the evaluation list. The Dragon Copilot integration makes it especially compelling for Microsoft-aligned health systems looking to combine ambient documentation with diagnostic insight. As a relatively young Series B company, expect a hands-on procurement and implementation experience.