Regard raised a $61 million Series B on July 11, 2024, led by Oak HC/FT. The company sells enterprise software that reviews electronic health-record data, surfaces potentially undocumented diagnoses with links to supporting evidence, and helps clinicians create more complete documentation. That can improve coding, quality reporting and reimbursement for care already delivered—but the system recommends conditions for human review; it is not an autonomous doctor or a consumer diagnostic app.
TechCrunch reported a valuation of about $350 million, citing a person familiar with the matter rather than a public filing. The round was a private financing event, not government funding or a public-company earnings announcement.
What happened in Regard’s 2024 funding round?
Regard announced the Series B on July 11, 2024. Oak HC/FT led the round, with participation from Cedars-Sinai Health Ventures, TenOneTen Ventures, Calibrate Ventures and Techstars. Regard said the money would help close gaps in clinical insight, reduce physician burden, improve safety and quality, and expand adoption and product development. No verified breakdown of the $61 million by hiring, research, sales or acquisitions was disclosed.
| Item | Reported detail |
|---|---|
| Round | Series B |
| Amount | $61 million |
| Announcement date | July 11, 2024 |
| Lead investor | Oak HC/FT |
| Other named investors | Cedars-Sinai Health Ventures, TenOneTen Ventures, Calibrate Ventures and Techstars |
| Reported valuation | Approximately $350 million, attributed by TechCrunch to a person familiar with the matter |
Regard was founded in 2017, and the company says its product launched in 2021. TechCrunch reported that revenue grew 4.5 times in 2023 and that management expected similar growth in 2024; those are CEO-provided, unaudited statements.
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What problem is Regard trying to solve?
Large EHRs contain notes, laboratory results, vital signs, medications, imaging, diagnoses and prior encounters. A clinician working under time pressure cannot manually reassess every data point at every visit. A relevant condition may therefore be absent from a current note, listed without enough specificity, or buried elsewhere in the chart.
Regard and TechCrunch have repeated a framing that physicians use only about 3% of available chart data. That figure is a company or industry talking point, not a universal measurement established for every clinician or EHR.
The practical consequences of incomplete documentation can include poorer care coordination, weaker quality reporting, inaccurate risk adjustment, avoidable coding queries and claims that do not fully represent the severity of care provided.
How the product works in a hospital
- Ingest and map data. Regard analyzes information from the health system’s EHR and maps it to a usable clinical record.
- Review the chart. Its software looks across notes, labs, medications, imaging and other available evidence.
- Recommend a possible diagnosis. The recommendation may address a condition that appears clinically supported but is missing, overlooked or documented too generally.
- Show the evidence. Regard says recommendations can be traced to source material so the clinician can inspect the basis for the suggestion.
- Let the clinician decide. A clinician can accept, edit, defer or reject the recommendation. Acceptance is a workflow event, not proof that a new disease was independently discovered.
- Update documentation. The resulting note or diagnosis can move into clinical-documentation-integrity, coding, quality, risk-adjustment and revenue-cycle processes.
Regard positions this as structured clinical reasoning and evidence linkage rather than an unrestricted language model producing a free-form summary. Its Clinical Notes materials say the system works within existing EHR workflows. Exact supported EHR products and implementation conditions depend on the buyer’s environment.
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What “find missed illness” means—and does not mean
- A condition may already be inferable from the record but absent from the active diagnosis list or current note.
- A diagnosis may be relevant but lack the specificity needed for care, coding or risk adjustment.
- The software can prompt investigation and confirmation; it cannot establish the diagnosis by itself.
- An absent diagnosis can also mean the condition was ruled out, documented elsewhere, or simply not present.
The safer description is “surfaces potentially missed or undocumented diagnoses for clinician review,” not “discovers disease autonomously.”
Why better documentation can increase hospital revenue
The financial pathway is indirect:
Chart evidence → clinician review → accurate documentation → coding, CDI and quality workflows → potentially better reimbursement or fewer denials.
More complete documentation can support an accurate severity-of-illness picture, appropriate diagnosis-related-group assignment, hierarchical condition category (HCC) risk adjustment and defensible claims. Earlier documentation may also reduce retrospective queries and identify care gaps, eligible procedures or consultations.
That does not authorize unsupported upcoding. A recommendation rejected by a clinician is not a billable or clinically established condition. Clinicians and coding professionals remain responsible for documentation and coding decisions, and Regard does not guarantee reimbursement or automatically change a claim.
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| Claim or metric | Source and qualification | What remains unknown |
|---|---|---|
| $61 million financing | Regard’s July 2024 announcement; financing fact | How the proceeds were allocated |
| 4.5× revenue growth in 2023 | CEO statement reported by TechCrunch | Audited results, revenue base and 2024 outcome |
| Thousands of clinicians, more than 150 hospitals and millions of recommended diagnoses | Company-reported figures in Regard and TechCrunch coverage | Definitions, time period and independent verification |
| 17% higher CC/MCC capture and 4× ROI per clinician at Sentara | Regard customer result published on its customer page | Baseline, costs included, study design and generalizability |
| More than 12.9 million accepted diagnoses; $50 million revenue earned; $9.3 million denials prevented; 20% fewer queries | Metrics displayed on Regard’s website and case studies | Denominators, dates, selection criteria and independent audit |
| More than 90% accuracy and two hours saved per clinician per day | Vendor claims on Clinical Notes | Reference standard, false-positive rate, specialty mix and validation methods |
These numbers indicate commercial traction and customer-reported value, not proof of improved mortality, morbidity, diagnostic accuracy across the market or repeatable net ROI. The reviewed material does not establish peer-reviewed validation, comparative trials or audited financial returns.
Who was using Regard in 2024?
TechCrunch reported signed health systems including Banner Health, Sentara Healthcare, Montefiore Medical Center and Cedars-Sinai. Regard said its software was in use across more than 150 hospitals. Those are company or publication-reported customer and footprint claims, not a market-share ranking.
How Regard compares with alternatives
TechCrunch identified 3M’s Engage One—now marketed as Solventum CDI Engage One—and Pieces as competitors in 2024. Solventum describes Engage One as an AI and natural-language platform for clinical intelligence, physician documentation, CDI worklists, evidence sheets and prioritization.
| Option | Typical strength | Important distinction |
|---|---|---|
| Regard | Chart-wide diagnosis recommendations combined with clinical notes, mid-revenue-cycle, HCC capture and screening workflows | Sales-led enterprise deployment; public pricing is unavailable |
| Solventum CDI Engage One | Broad CDI and revenue-cycle ecosystem, including query and worklist workflows | Especially relevant for organizations considering Solventum’s wider stack |
| EHR-native tools | Existing data access and familiar interfaces | Capabilities vary by EHR and module |
| Ambient scribes | Generate notes from patient-clinician conversations | Conversation capture is not the same as chart-wide diagnostic review |
| Human CDI teams and retrospective review | Contextual judgment and established governance | Labor-intensive and less continuous |
| Internal analytics or rules engines | Customization to local workflows and data | Requires in-house engineering, validation and maintenance |
No independent evidence in the available material establishes a market leader. Regard’s claimed differentiator is the combination of chart analysis, point-of-care documentation and downstream financial workflows.
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Risks hospitals should evaluate
False positives and alert fatigue
Weak suggestions can add clicks, erode clinician trust and undermine productivity. Buyers should request precision, rejection rates, alert volume and acceptance rates by diagnosis category—not only total recommendations accepted.
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Automation bias
An EHR-integrated suggestion can appear authoritative. Clinicians need to see the underlying evidence and retain responsibility for confirming, editing or rejecting it.
Incomplete or distorted data
AI cannot recover information that is missing, delayed, incorrectly mapped or trapped in scanned documents, outside records, handwritten notes or unintegrated systems.
Site and specialty variation
A model validated in one hospital may perform differently in rural, community or academic settings, across specialties, or with another EHR configuration. Site-specific testing and ongoing monitoring are essential.
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Compliance and privacy
Regard says it is HIPAA-compliant and SOC 2 Type II certified. Those are company statements; a buyer should obtain current audit documentation, business-associate terms, access controls, retention and deletion rules, subcontractor details, model-training policies and incident history. Revenue-focused workflows also require controls against unsupported diagnoses and upcoding.
Implementation and vendor dependence
Regard says a typical go-live takes six to 10 weeks, a vendor estimate rather than a guarantee. Real deployment also involves data mapping, security review, clinician training, change management, downtime procedures, model monitoring and contract terms for termination, audit rights and data portability. Combining diagnosis intelligence with an ambient scribe or revenue-cycle platform may improve workflow, but it concentrates accountability and integration risk.
Questions to ask before signing
- How is accuracy defined, and what reference standard was used?
- What are false-positive and false-negative rates by specialty, site and patient group?
- Can clinicians inspect the exact evidence for every recommendation?
- Does the workflow create alerts or extra clicks, and how are rejected suggestions handled?
- Which EHR versions and note types are supported?
- Is ROI measured per clinician, encounter, bed or enterprise, and does it include subscription, integration and training costs?
- How are model updates governed, monitored and rolled back?
- Is patient data used to train models, and what are the retention and deletion rules?
- What is the escalation process for unsafe recommendations or patient-safety incidents?
What changed after the 2024 financing?
Regard’s later announcements should not be read back into the Series B product description. On July 21, 2025, the company announced a platform combining EHR chart data with patient-physician conversations and introduced its Max AI agent: Regard’s announcement. In 2026, Regard announced a relationship involving Microsoft Dragon Copilot at HIMSS: PR Newswire. These updates signal broader clinical-AI positioning, but they do not independently prove effectiveness or establish that every feature was available in July 2024.
What hospitals can buy—and what they cannot assume
Regard’s current offering is an enterprise, sales-led product spanning Clinical Notes, Mid-Revenue Cycle, HCC Capture and Screening. The company’s demo page requests organizational and EHR information. No public price, free trial or self-serve plan is listed, so individual physicians, consumers and small practices should not treat it as a personal diagnostic app.
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Regard’s investment case sits where clinical documentation, physician workflow and revenue integrity overlap. The $61 million round demonstrates investor and commercial confidence, while the harder question remains whether each hospital can validate accuracy, safety, compliance and net financial value after integration and adoption costs.
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