Attestiv
AI- and forensics-based media validation platform that screens photos, video, audio, and documents for deepfakes and tampering before they influence claims, lending, and compliance decisions.
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Attestiv, founded in 2018 and based in the Boston area, sells a media-forensics platform called DeepScan that screens photos, video, audio and documents for signs of manipulation before they are used to approve insurance claims, loan applications, or compliance filings. The system combines AI-based deepfake detection with forensic signal analysis, metadata inspection and duplicate/reuse checks, then scores each submitted file against the organization’s own business and claims data rather than analyzing the file in isolation.
The product is delivered through APIs and SDKs that plug into existing claims, underwriting and lending workflows, routing flagged content into pass/flag/request-more-information/escalate outcomes rather than a simple yes/no verdict. Attestiv has disclosed a partnership with insurance platform vendor PCMS for automated fraud detection and lists logos including Insurity, Duck Creek and Cognizant, though it does not publish named customer case studies or independent accuracy figures.
With roughly $8-10M raised across nine rounds since 2018 and a headcount in the 11-50 range, Attestiv remains a small, vertically focused vendor in a media-authentication space that has grown more crowded as generative AI has made fabricated claims documentation and deepfaked verification media easier to produce.
Innovation Matrix Assessment
Steady feature cadence (e.g. a 2025 'AI-powered Context Analysis' update) but no evidence of rapid, repeatable breakthroughs since 2018 founding.
API/SDK integration into existing claims and underwriting workflows gives real operational value to fraud and claims teams, though the use case is narrower than core security operations.
Only ~$8-10M raised across nine rounds since 2018, a small (11-50 employee) team, and no named enterprise case studies — modest, not strong, adoption evidence.
A point solution for media authentication within insurance/lending verticals; it does not change how media authentication is approached industry-wide.
No independent accuracy testing or named incident response found; the company publishes no customer-verified detection metrics.
Deepfake-driven fraud in claims and lending is a growing, durable problem, keeping the use case relevant over the medium term.
Why CISOs Should Care
Gives fraud, claims, and compliance teams an automated first line of defense against AI-generated fake documentation and media before it enters financial workflows.
What Makes It Different
Validates submitted media against the organization's own business and claims data, not just the file's internal forensic signals, and routes results into a configurable workflow rather than a binary verdict.
The Matrix Verdict
52/100 — INCREMENTAL INNOVATOR
An Incremental Innovator: a real, functioning product with legitimate vertical use cases in insurance and lending, but modest funding, no independent efficacy evidence, and a narrow, non-disruptive scope keep it in the lower-middle of the Matrix.
Editorial Note: Claims vs. Verified Findings
Vendor claims about detection validation against 'large datasets' and third-party award mentions (e.g. an F6S ranking) are self-reported; no independently verified accuracy figures or named customer outcomes were found.
Sources
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