Scaling Resemble AI’s Real-Time Deepfake Detection Models with Cerebrium

Resemble AI uses deepfake detection models for real-time audio, image, and video workflows such as live calls, identity verification, and fraud prevention, where delays or outages can have immediate consequences. Drawing on its experience developing generative technology, including the widely downloaded Chatterbox voice models, the company studies evolving synthetic-media attacks and rapidly updates its detectors to address new threats. To overcome limitations with cold starts, reliability, varied model hardware needs, and regional data-residency requirements, Resemble AI moved its workloads to Cerebrium’s serverless GPU infrastructure. The platform enables rapid scaling, low-latency deployments, multi-region availability, failover support, and integration with existing Docker and CI/CD workflows without requiring researchers to manage GPU fleets. Resemble AI says the infrastructure has allowed it to release updated detection models weekly or more often, support customers across the United States, United Kingdom, and European Union, and focus more engineering resources on improving its detection, watermarking, and identity-related systems.

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