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← Video Delivery & CDN
CDNProduct LaunchJune 9, 2026

Steg AI Launches API for Forensic Watermarking, Deepfake Shielding in Video

Steg AI Launches API for Forensic Watermarking, Deepfake Shielding in Video
Steg

Steg AI launched its API, allowing developers to integrate forensic, visible watermarking, and deepfake shielding directly into their applications. The API supports various asset types, including video formats like MOV and MP4, facilitating content protection and authenticity verification for streaming professionals. This technical documentation provides comprehensive details on authentication, asset management, encoding/decoding processes, and webhook subscriptions.

Key Takeaways

  • Steg AI's new API offers forensic watermarking, visible watermarking, and deepfake shielding capabilities.
  • The API supports various asset types, including video formats such as MOV and MP4.
  • Features include authentication, asset management, encoding/decoding, and webhook subscriptions.
  • The deepfake shield specifically protects content from AI manipulation to maintain integrity.
  • Batch encoding and decoding of up to 50 assets per request is supported.

Why It Matters

The introduction of a programmatic interface for content authentication and protection tools directly addresses the rising concerns around content authenticity and AI-generated media. By enabling direct integration into existing workflows, Steg AI lowers the barrier for streaming platforms and content creators to deploy sophisticated anti-piracy and deepfake countermeasures. The industry will be watching for adoption rates and how effectively this API deters unauthorized distribution and AI manipulation of high-value video content.

Additional Context

The launch of Steg AI's API comes as the streaming industry confronts increasing challenges from deepfakes and AI-generated content. According to a report by AI Foundation in March 2026, over 70% of media executives surveyed expressed concern about the proliferation of deceptive AI content impacting trust in their platforms. Earlier this year, a study published by the University of California, Berkeley (February 2026) demonstrated that forensic watermarking techniques, similar to those offered by Steg AI, were able to identify the source of leaked content with 98% accuracy in test environments. This follows a trend of content security providers enhancing their offerings; for example, Intertrust announced new AI-driven piracy detection tools in April 2026, and Verify.ly released a content provenance system in May 2026 focusing on blockchain-based verification. These developments highlight a broader industry move towards robust, API-first solutions for content integrity, as reported by TechCrunch in April 2026.


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