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Automatic Content Recognition
for any video content

Platforms

Moderate user-generated videos and live streams at scale by detecting copyrighted, criminal, and duplicated content

Rightsholders

Protect your library by scanning the largest video platforms for unauthorized copies

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What is Automatic Content Recognition

Automatic Content Recognition is an advanced technology that uses algorithms to analyze and identify criminal and copyrighted videos among user-generated content. Each upload on your platform is checked against the reference database of criminal or copyrighted materials. If the upload matches the content in the reference database, you get notified about the match. Get visibility over what is available on your platform in real-time.

Adult
Duplicate
Copyrighted
Unique
Criminal

How ACR software works

The content recognition is based on WebKyte’s proprietary video fingerprinting technology. It’s like giving each video a unique digital ID, so it’s easy to identify its copies fast and accurate.

Every upload on a platform is converted in a binary form. The generated fingerprints are then checked against the reference database to detect copyrighted, illegal, and adult content. The matching results are returned in real-time. Rapid matching is achieved regardless of the video quality, audio, and different distortions.

The main technology extracts distinctive elements of a video into a unique line of code, a digital fingerprint. The tech enables video matching at large scale, high speed, and with extraordinary accuracy.

Single-frame fingerprints are combined to form a comprehensive digital fingerprint of the entire video.

Who can use ACR software

UGC platforms benefit the most from using this type of software. With the single ACR solution, video platforms can moderate video materials, comply with official regulations, and improve the experience for viewers, creators, and advertisers.

Automated content recognition in live-streaming

To protect time-sensitive Live Events (sports, awards, and concerts), video platforms can moderate live streams using WebKyte software. ACR software fingerprints every user-generated live stream happening on a platform and compares these fingerprints with an official stream of a Live Event. The matching results are returned in real time.

Why video platforms select WebKyte for content recognition

As the digital media landscape evolves, choosing the right video content moderation tool is crucial. WebKyte’s software stands out for its unparalleled efficiency and accuracy. Here’s why it’s the top choice for media platforms:

Fast video matching

WebKyte’s software enables swift content matching with real-time results, extensively reducing false positives.

High accuracy

Criminal or adult content can drive away users and reduce their engagement. By creating a safe content library, platforms foster an environment that encourages users’ loyalty and retention.

Attract more partners and advertisers

Designed for large-scale operations, our technology correctly handles extensive volumes of materials, making it suitable for platforms with any number of uploads.

Enhanced security

Video fingerprints provide top-tier content security. They are irreversible, ensuring the original files remain unidentified without metadata.

Cost-effectiveness

The software eliminates the need for large analyst teams, allowing a single content security professional to manage extensive content, thereby saving costs.

Distortion resistance

Our technology is robust against various distortions. It identifies content based on video frames, regardless of metadata, audio changes, or video alterations.

Detect illegal videos before they go public

Get notified when harmful, adult, or misleading content is uploaded to keep the platform’s brand and viewers safe.

Prevent
copyright claims

Instantly identify copyrighted content among user-uploaded videos

Сomply
with Article 17 EU

Meet existing and upcoming regulations by enhancing your platform’s content identification capabilities

Empower
your platform
with WebKyte





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