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Content Hub › Software & Platforms

DigitalOwl — Profile & Assessment

DigitalOwl operates in the medical-record review ecosystem, within the AI-native / Tech-enabled service, Insurance / Legal segment. This profile records what the company publishes about its services, maps those claims to the Content Hub evaluation rubric, and cites every source behind them. 14 of 17 facts are confirmed from 17 public sources; unpublished fields are marked, never estimated.

4 sections·17 sources·Verified 2026-08-21 ✓
Disclosure
14/17 facts
01

What it does

AI platform converting medical records into structured data for insurance and legal review: 'View' (AI medical summaries/360° history), 'Chat' (conversational Q&A over records), 'Triage' (automated flagging/audit reports), 'Workflows' (AI decision trees), 'Connect' (data API), 'Case Notes' (line-of-business-specific insights). Everything above is drawn from the 17 public sources cited at the foot of this page. Fields the company does not publish are marked as unpublished below rather than estimated.

02

Evaluation criteria

Disclosure across the hub318 vendors profiled
12345median678

DigitalOwl publishes 6 of the 8 fields in the rubric. Across the 318 vendors profiled in this hub the median is 5. 22 of the 318 publish more; 55 publish exactly as many.

Content Hub rubric6 of 8 published
Processing model
100% AI (self-serve medical record review)
Human QA
None disclosed
Typical turnaround
Delivery within 24 hours (self-serve)
Pricing model
Subscription (self-serve monthly plan, capped by page volume)
Indicative cost
No published rate: no dollar figures published. The Enterprise vs. Self-Serve (<30,000 pages/month) split is the only pricing-relevant signal, implying volume/page-based tiering with a defined self-serve ceiling before enterprise sales engagement is required.
Export formats
Not published
Best for
Fast triage of medical records for legal teams (self-serve, under 30,000 pages/month)
Customer satisfaction
No public reviews found
03

Profile notes

Who it serves
Life insurance underwriting/claims/post-issue audit; P&C insurance (bodily injury, workers' comp); legal (personal injury, mass tort, medical malpractice)
Claims & platform notes
Site claims 97% accuracy rate, up to 72% time savings in medical review, and 90% reduction in page count via deduplication. Underlying model architecture Not published. Named clients: RGA, Simplicity Group, SelectX, AAA Life Insurance, Dynacare, Ethos, Legal & General, American Family Insurance, Nationwide, Verus
Review summary
Verdict: worthwhile for insurers and legal teams already inside Datavant's record-retrieval ecosystem. Evidence: vendor site claims 97% accuracy and 90% page-count reduction via deduplication; the 2026-07-19 traffic analysis documents the Datavant acquisition and the DigitalOwl/ChartSwap/Datavant brand tracking requirement.
04

What to confirm before you sign

DigitalOwl publishes 6 of the 8 fields in the Content Hub rubric. Across all 318 vendors profiled in the Content Hub, the median is 5 of 8. The gaps below are not marks against the vendor — most of this industry quotes on request. They are simply the questions you still have to ask, and the answers are worth getting in writing before a file changes hands.

  1. What does a real 1,000-page file cost, all in?
    Ask for a worked example rather than a rate card. Duplicate pages, rush fees and monthly minimums are where the quoted rate and the final invoice separate.
    Indicative cost83% of all profiled vendors leave this unpublishedOurs: 10¢ a page, duplicates free
  2. What formats does the deliverable come in, and do the citations survive export?
    Ask to see an exported file rather than a screen share. A citation that works inside the vendor's viewer and dies in Word is not a citation you can file.
    Export formats92% of all profiled vendors leave this unpublishedOurs: DOCX or HTML, every citation stays a live link
  3. Where do the records live, and who signs the BAA?
    Protected health information is going to leave your office. Ask which entity holds it, in which country, and who is on the hook if it leaks.
  4. Is my data used to train a model?
    Ask for the answer in the contract rather than the sales call, and check whether it also binds their subprocessors.

Key facts

Segment

AI-native / Tech-enabled service, Insurance / Legal

Website

https://www.digitalowl.com

Founded

2017

HQ

New York, NY — exact street address Not published

Headcount

51–100 employees

Ownership

Acquired by Datavant (per site branding: 'A Datavant Company'). Prior to acquisition, Crunchbase shows 4 funding rounds including a Series B led by Reinsurance Group of America (RGA), plus a Series A and Seed; other investor Ibex Investors. Amounts Not published (obfuscated on free Crunchbase view).

Turnaround

Claims '<1 hour turnaround for processing thousands of pages' (per site)

Certifications

HIPAA and SOC 2 compliant (per site, 'comprehensive privacy program')

Not publishedPricing

Sources

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Last verified: 2026-08-15