100% file review. Not a 5% sample.
The IME says full duty. The treating physician says no lifting. OwlVision reads 100% of every file, flags contradictions and ODG deviations, and cites every finding to the page.
What a 100% read finds that a sample review can’t.
Every finding cites the page it came from, so adjusters and auditors verify it in seconds. Your newest adjuster gets your best adjuster’s read, on every file.
Contradictions across documents
Page 40 against page 412. The FNOL recording against the medical records. The IME against the treating physician. Flagged before the decision, not after.
Guideline deviations
Treatment running past ODG guidelines is the most expensive thing hiding in a comp file, and the hardest to spot by hand. Flagged, with the source cited.
Every file, not a sample
100% review coverage. Guideline overruns, missed subrogation and contradictions found after the decision are leakage you are already paying for.
Measured in production, not in a pilot deck.
Figures from Owl production deployments. Detail and methodology shared during the back-test read-out.
96%
extraction accuracy on 18,400 hand-labelled documents
92%
concordance with independent medical examiners
100%
review coverage, every file and every page
$3.8M
in recoveries surfaced per 100K files
Bring a closed quarter. Leave with a dollar figure.
Scoping call to read-out · under two weeks
Pick a closed quarter
You choose the cohort: a quarter of closed comp files, de-identified as far as you need. Everything runs under NDA, inside a dedicated tenant, and your data never trains our models.
We run OwlVision on it
Every file read end to end, every contradiction and guideline deviation flagged and cited. No integration; a document export is enough.
You get the number
A read-out with a claims engineer: what was found, on which files, cited to the page, and what it was worth in leakage and recoveries.
100% file review. Not a 5% sample.
You audit a sample because you can’t audit everything. OwlVision can: every file, every page, every contradiction flagged with a citation, without a data-science team to run it. Pilots reach production readiness in under two weeks. Back-test on a closed quarter first and see what the sample missed before you commit to anything.
- —Every file in the quarter read end to end, with contradictions and ODG deviations flagged
- —Every finding cited to its page, so your team can verify it
- —A dollar figure: the leakage and recoveries the sample review missed
- —A written read-out you can take to your VP or your board