SoundPatrol⁽ᵀᴹ⁾
SoundPatrol⁽ᵀᴹ⁾
A large-scale 24/7 surveillance system to keep track of unlicensed activity (copyright infringement).
A neural fingerprinting scanner that is completely AI-native and has large GPU clusters at its disposal.
A large-scale 24/7 surveillance system to keep track of unlicensed activity (copyright infringement).
A neural fingerprinting scanner that is completely AI-native and has large GPU clusters at its disposal.
Catalog Restoration For Models
An end-to-end AI pipeline that ingests legacy audio files, learns their noise and artifact profiles, and applies spectral inpainting and learned denoising models to reconstruct high-fidelity waveforms. Outputs are normalized, metadata-aligned audio segments ready for downstream training, analysis, or generative tasks.
Adversarial Model Building
An end-to-end AI pipeline that ingests legacy audio files, learns their noise and artifact profiles, and applies spectral inpainting and learned denoising models to reconstruct high-fidelity waveforms. Outputs are normalized, metadata-aligned audio segments ready for downstream training, analysis, or generative tasks.
Music AI detection
A neural-powered classification system that analyzes acoustic, spectral, and performance-style features to distinguish between human-played and AI-generated music. By combining deep audio embeddings with behavioral cues—such as micro-timing variations, expressive dynamics, and artifact fingerprints—our models deliver per-track likelihood scores and segmented heatmaps, enabling rights holders and platforms to verify authentici
Voice DNA Engines
Using high-resolution spectral embeddings, we create unique “vocal fingerprints” that can identify, classify, and authenticate voices across vast datasets. This technology supports artist attribution, deepfake detection, and personalized vocal assistant use-cases.
Large Music Foundation Models
We can make your data into a scalable, open-ended music LLM, pre-trained on diverse audio, MIDI, and metadata sets—ready to power applications in composition, style transfer, and data augmentation. Fine-tune them on your proprietary catalog for bespoke generative and analytical workflows.
Catalog Protection
We deploy neural-fingerprinting and watermarking solutions to fingerprint every track in your catalog, enabling real-time detection of unauthorized uses across the web. Potentially combined with blockchain-backed metadata, this service guarantees provenance, attribution, and auditable usage logs.
Dynamic Watermarking with Interlocking Neural Fingerprinting Scanners
An adaptive, imperceptible watermark is embedded into each track stream at the codec or server level, where the watermark parameters (e.g., frequency bands, phase shifts, or spread-spectrum patterns) change dynamically per user session or time window. Downstream, a network of neural-powered fingerprinting scanners—trained to recognize both the underlying audio fingerprint and the evolving watermark signatures—continuously cross-checks incoming uploads or re-streams. The neural models adapt to signal distortions, remixes, or transcoding, maintaining robust detection even under adversarial attacks.
AI Agent Enforcement
An end-to-end AI pipeline that ingests legacy audio files, learns their noise and artifact profiles, and applies spectral inpainting and learned denoising models to reconstruct high-fidelity waveforms. Outputs are normalized, metadata-aligned audio segments ready for downstream training, analysis, or generative tasks.
StreamPatrol⁽ᵀᴹ⁾
StreamPatrol⁽ᵀᴹ⁾
A highly advanced, server-side stream protection system with war and combat rooms during the live sports broadcast event.
This is the state-of-the-art technology used to combat piracy for premium live and on-demand video content.
A highly advanced, server-side stream protection system with war and combat rooms during the live sports broadcast event.
This is the state-of-the-art technology used to combat piracy for premium live and on-demand video content.
Per-viewer audio watermark
A unique, inaudible tag is embedded into each user’s audio stream. Survives recording, compression, and re-streaming.
Unique internal key per viewer
Each session is encrypted with a key tied to that specific account, stopping credential sharing.
Edge-side processing at the CDN
Watermark insertion and encryption happen on-the-fly when the OTT box requests a segment.
No changes to OTT devices
All logic runs in the CDN path; set-top boxes operate exactly as they do today.
SoundPatrol⁽ᵀᴹ⁾
A large-scale 24/7 surveillance system to keep track of unlicensed activity (copyright infringement).
A neural fingerprinting scanner that is completely AI-native and has large GPU clusters at its disposal.
Catalog Restoration For Models
An end-to-end AI pipeline that ingests legacy audio files, learns their noise and artifact profiles, and applies spectral inpainting and learned denoising models to reconstruct high-fidelity waveforms. Outputs are normalized, metadata-aligned audio segments ready for downstream training, analysis, or generative tasks.
Adversarial Model Building
An end-to-end AI pipeline that ingests legacy audio files, learns their noise and artifact profiles, and applies spectral inpainting and learned denoising models to reconstruct high-fidelity waveforms. Outputs are normalized, metadata-aligned audio segments ready for downstream training, analysis, or generative tasks.
Music AI detection
A neural-powered classification system that analyzes acoustic, spectral, and performance-style features to distinguish between human-played and AI-generated music. By combining deep audio embeddings with behavioral cues—such as micro-timing variations, expressive dynamics, and artifact fingerprints—our models deliver per-track likelihood scores and segmented heatmaps, enabling rights holders and platforms to verify authentici
Voice DNA Engines
Using high-resolution spectral embeddings, we create unique “vocal fingerprints” that can identify, classify, and authenticate voices across vast datasets. This technology supports artist attribution, deepfake detection, and personalized vocal assistant use-cases.
Large Music Foundation Models
We can make your data into a scalable, open-ended music LLM, pre-trained on diverse audio, MIDI, and metadata sets—ready to power applications in composition, style transfer, and data augmentation. Fine-tune them on your proprietary catalog for bespoke generative and analytical workflows.
Catalog Protection
We deploy neural-fingerprinting and watermarking solutions to fingerprint every track in your catalog, enabling real-time detection of unauthorized uses across the web. Potentially combined with blockchain-backed metadata, this service guarantees provenance, attribution, and auditable usage logs.
Dynamic Watermarking with Interlocking Neural Fingerprinting Scanners
An adaptive, imperceptible watermark is embedded into each track stream at the codec or server level, where the watermark parameters (e.g., frequency bands, phase shifts, or spread-spectrum patterns) change dynamically per user session or time window. Downstream, a network of neural-powered fingerprinting scanners—trained to recognize both the underlying audio fingerprint and the evolving watermark signatures—continuously cross-checks incoming uploads or re-streams. The neural models adapt to signal distortions, remixes, or transcoding, maintaining robust detection even under adversarial attacks.
AI Agent Enforcement
An end-to-end AI pipeline that ingests legacy audio files, learns their noise and artifact profiles, and applies spectral inpainting and learned denoising models to reconstruct high-fidelity waveforms. Outputs are normalized, metadata-aligned audio segments ready for downstream training, analysis, or generative tasks.
StreamPatrol⁽ᵀᴹ⁾
A highly advanced, server-side stream protection system with war and combat rooms during the live sports broadcast event.
This is the state-of-the-art technology used to combat piracy for premium live and on-demand video content.
Per-viewer audio watermark
A unique, inaudible tag is embedded into each user’s audio stream. Survives recording, compression, and re-streaming.
Unique internal key per viewer
Each session is encrypted with a key tied to that specific account, stopping credential sharing.
Edge-side processing at the CDN
Watermark insertion and encryption happen on-the-fly when the OTT box requests a segment.
No changes to OTT devices
All logic runs in the CDN path; set-top boxes operate exactly as they do today.
Sound
Patrol⁽ᵀᴹ⁾
SoundPatrol⁽ᵀᴹ⁾
SoundPatrol⁽ᵀᴹ⁾
A large-scale 24/7 surveillance system to keep track of unlicensed activity (copyright infringement).
A neural fingerprinting scanner that is completely AI-native and has large GPU clusters at its disposal.
Catalog Restoration For Models
An end-to-end AI pipeline that ingests legacy audio files, learns their noise and artifact profiles, and applies spectral inpainting and learned denoising models to reconstruct high-fidelity waveforms. Outputs are normalized, metadata-aligned audio segments ready for downstream training, analysis, or generative tasks.
Adversarial Model Building
An end-to-end AI pipeline that ingests legacy audio files, learns their noise and artifact profiles, and applies spectral inpainting and learned denoising models to reconstruct high-fidelity waveforms. Outputs are normalized, metadata-aligned audio segments ready for downstream training, analysis, or generative tasks.
Music AI detection
A neural-powered classification system that analyzes acoustic, spectral, and performance-style features to distinguish between human-played and AI-generated music. By combining deep audio embeddings with behavioral cues—such as micro-timing variations, expressive dynamics, and artifact fingerprints—our models deliver per-track likelihood scores and segmented heatmaps, enabling rights holders and platforms to verify authentici
Voice DNA Engines
Using high-resolution spectral embeddings, we create unique “vocal fingerprints” that can identify, classify, and authenticate voices across vast datasets. This technology supports artist attribution, deepfake detection, and personalized vocal assistant use-cases.
Large Music Foundation Models
We can make your data into a scalable, open-ended music LLM, pre-trained on diverse audio, MIDI, and metadata sets—ready to power applications in composition, style transfer, and data augmentation. Fine-tune them on your proprietary catalog for bespoke generative and analytical workflows.
Catalog Protection
We deploy neural-fingerprinting and watermarking solutions to fingerprint every track in your catalog, enabling real-time detection of unauthorized uses across the web. Potentially combined with blockchain-backed metadata, this service guarantees provenance, attribution, and auditable usage logs.
Dynamic Watermarking with Interlocking Neural Fingerprinting Scanners
An adaptive, imperceptible watermark is embedded into each track stream at the codec or server level, where the watermark parameters (e.g., frequency bands, phase shifts, or spread-spectrum patterns) change dynamically per user session or time window. Downstream, a network of neural-powered fingerprinting scanners—trained to recognize both the underlying audio fingerprint and the evolving watermark signatures—continuously cross-checks incoming uploads or re-streams. The neural models adapt to signal distortions, remixes, or transcoding, maintaining robust detection even under adversarial attacks.
AI Agent Enforcement
An end-to-end AI pipeline that ingests legacy audio files, learns their noise and artifact profiles, and applies spectral inpainting and learned denoising models to reconstruct high-fidelity waveforms. Outputs are normalized, metadata-aligned audio segments ready for downstream training, analysis, or generative tasks.
StreamPatrol⁽ᵀᴹ⁾
StreamPatrol⁽ᵀᴹ⁾
StreamPatrol⁽ᵀᴹ⁾
A highly advanced, server-side stream protection system with war and combat rooms during the live sports broadcast event.
This is the state-of-the-art technology used to combat piracy for premium live and on-demand video content.
Per-viewer audio watermark
A unique, inaudible tag is embedded into each user’s audio stream. Survives recording, compression, and re-streaming.
Unique internal key per viewer
Each session is encrypted with a key tied to that specific account, stopping credential sharing.
Edge-side processing at the CDN
Watermark insertion and encryption happen on-the-fly when the OTT box requests a segment.
No changes to OTT devices
All logic runs in the CDN path; set-top boxes operate exactly as they do today.