Evidently vs Regard
Two Revenue Integrity & Pre-Bill Review vendors, side by side. Facts from public sources; judgments are ours.
At a glance
Derived from public facts · a rough scale, not a ranking
| Evidently | Regard | |
|---|---|---|
| Pricing model | Enterprise contract (custom) · Pricing not published | Not published · Health system contracts |
| Speed to go live | SMART on FHIR pilot, then rollout | System-wide EHR embed with chart data access |
| Automation model | AI copilot · Surfaces evidence, humans decide | AI copilot · diagnosis suggestions inside the chart |
| Built for | Mid-size groups, Enterprise systems | Enterprise systems |
| Security posture | SOC 2 Type II, HIPAA | No certifications published |
| Company maturity | 6 yrs (est. 2020) | 9 yrs (est. 2017) |
| Financial backing | $15M · Series A | $80M+ · Series B |
| Named customers | 3 named | 4 named |
| Published results | No public numbers | No public numbers |
| Documented integrations | 4 listed | 1 listed |
| Third-party validation | KLAS / analyst cited | None found |
Bottom line
- Pick Evidently if you want one EHR-embedded chart intelligence layer serving clinicians, CDI, and risk adjustment together.
- Pick Regard if you run a hospital or health system and want an EHR-embedded copilot that surfaces missed diagnoses and drafts documentation for clinicians.
Evidently
EHR-embedded AI that turns scattered chart data into answers
- Founded
- 2020
- HQ
- San Francisco, CA
- Stage
- Series A
- Raised
- $15M
What it does
- AI chart summarization inside the EHR
- Ask Evidently chat pre-loaded with full chart
- CDI review and denial appeal support
- HCC capture and care gap reconciliation
- Note drafting for admits and discharges
- Registry abstraction and pre-op review
Where it's strong
- One chart-intelligence layer serves clinicians, CDI teams, and value-based care, spreading cost across use cases.
- Named academic and health system customers with third-party validation, including a 31.7-point Net EHR Experience Score gain at Iowa measured by KLAS.
- Allina Health documented 6x ROI on the value-based care use case.
What buyers should weigh
- Deep EHR embedding means IT involvement and a real pilot; UNC ran 12 weeks before enterprise rollout.
- It surfaces documentation and HCC opportunities but does not autonomously code or bill.
- At $15M raised it is a smaller vendor taking on well-funded CDI incumbents.
Named customers
University of Iowa Health Care · Allina Health · UNC Health
Integrations
Regard
AI that surfaces undocumented diagnoses in the workflow
- Founded
- 2017
- HQ
- Los Angeles, CA
- Stage
- Series B
- Raised
- $80M+
What it does
- Reviews the full patient chart inside the EHR
- Surfaces missed or undocumented diagnoses to clinicians
- Drafts clinical notes with supporting evidence linked
- Runs concurrently during the stay, not post-discharge
- Improves documentation for both revenue and quality metrics
Where it's strong
- Works concurrently inside the clinician's Epic workflow, so diagnoses are captured while the physician can still act on them, unlike post-discharge review tools.
- Multi-year, system-wide proof: Sentara scaled to all 12 hospitals after 2-4x ROI, and Banner rolled it toward 33 hospitals.
- Cedars-Sinai is investor, development partner, and customer, giving unusual clinical depth for a company this size.
What buyers should weigh
- Requires physician adoption to deliver value, a harder change-management lift than back-office tools your clinicians never see.
- Smaller war chest (roughly $80M raised) than several competitors chasing the same documentation dollars.
- Value proposition mixes clinical decision support with revenue capture; make sure your compliance team is comfortable with how diagnosis suggestions are framed.
Named customers
Cedars-Sinai · Banner Health · Sentara Health · WakeMed Health & Hospitals
Integrations
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