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A NEW CLASS OF INSURANCE FRAUD
Seeing is no longer believing.
AI-made medical receipts already enter claims. Frodau catches them before payout.

Expose fraud. Save millions.
Fabricated on demand. No scanner, no scissors, no glue.
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Invisible to the human eye
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Detection is just emerging
How it works
One upload. Four answers.
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Duplicate?
Fingerprint memory across the organization. Cropped, re-shot, or lightly edited: never paid twice.

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Medical?
Pharmacy, clinic, dental, lab, or not medical at all. Non-medical uploads flag immediately.

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Covered?
Every line is marked covered, excluded, or uncertain. The snack does not ride with the drug.

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Real?
Independent forensic and AI detectors decide: original photo, edited file, or machine-made.

Built for speed: detectors run in parallel when the two commercial AI engines strongly agree, slower checks are skipped entirely.
No single detector decides alone.
Metadata forensics
Camera EXIF, editing traces, AI-generator signatures inside the file
Compression analysis ELA
Heatmaps expose pasted or altered regions the edited total, the classic
Two independent AI detectors
Two commercial engines score the same question: was this made by a machine?
Synthetic pattern analysis
Pixel- and style-level signals typical of generative models, not real photography
Semantics & arithmetic
Do the lines add up? Are dates, times, VAT and totals internally consistent?
Medical identifier validation
Provider and drug identifiers, copays and insurance data pass plausibility checks
Visual cross-examination
A vision model gives a second opinion: does the document's story hold?
Duplicate memory
Fingerprint matching against everything the organization has already seen
Careful verdicts, not accusations.
- Likely genuine
- Needs review
- Likely fake / AI
- Inconclusive
What Frodau delivers
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See the invisible
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Focus your reviewers
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End resubmissions
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Defensible decisions
Our proposal: a controlled pilot on your historical claims.
In days, not months we run Frodau on cases you've already handled, show exactly what it would have been flagged in real time, and calculate the true savings potential together.
The question we want to test with you: can Frodau help identify and prevent up to ₪100M in incorrect payments and fraud over time? If we find even a fraction of what we believe is hiding in the data it's millions.
AI product meets fraud intelligence.
A team built for exactly this problem.

Yan Chelly
Co-founder · CEO & CTO
20+ years in product, technology and AI at global companies. VP Product at Air Doctor; formerly Fiverr and eBay, with deep computer-vision experience; ex-CPO at enso, an autonomous AI-agents platform. Two registered patents in AI and commerce.

Kfir Shado
Co-founder · CRO
~15 years in intelligence, investigations and fraud detection. Specialist in rapid risk identification and analysis.