Defensive Security & Blue Team SecurityWeek 2 weeks ago

Modulate Raises $25 Million to Advance Deepfake Detection

CN
CyberNew Threat Research Desk
• Original Reporting: SecurityWeek
CyberNew Threat Intel Assessment
Assessed Severity: INFORMATIONAL
Impacted Surface
Enterprise Perimeter & Network Defense
Intelligence Sector
Defensive Security & Blue Team

Analyst Takeaway

"Frontier AI firm Modulate has raised an additional $25 million funding from Future Ventures, with participation from Hyperplane and Lakestar, bringing its total funding to $60 million. Modulate builds audio-native AI models that enable machines to understand the nuances in human conversation, whether natural or fake. It uses a proprietary Ensemble Listening Model (ELM) architecture to generate..."

Recommended Defense & Mitigation

  • Threat Monitoring: Ingest published IOCs into SIEM/EDR detection rules for continuous telemetry monitoring.
  • Security Awareness: Alert staff and maintain baseline endpoint hardening across endpoints.
Curated & Verified by CyberNew Threat Intelligence Desk Standard Defense Framework (NIST / MITRE ATT&CK)

Frontier AI firm Modulate has raised an additional $25 million funding from Future Ventures, with participation from Hyperplane and Lakestar, bringing its total funding to $60 million. Modulate builds audio-native AI models that enable machines to understand the nuances in human conversation, whether natural or fake. 

It uses a proprietary Ensemble Listening Model (ELM) architecture to generate the individual AI models that power its Velma platform. Velma brings together more than 100 of these specialized models that understand and detect signals including emotion, tone, intent, synthetic speech and conversational behavior.

The firm currently analyzes more than 10 million hours of audio each month, with over 600 million hours analyzed in total. According to Modulate, its transcription and deepfake detection models both ranked #1 on public benchmarks like Hugging Face.

Modulate focuses on using AI to analyze voice rather than create voice. It claims its Velma platform results are twice as accurate as traditional LLMs and generate seven times fewer false positives. Since Velma operates in real time, applications built with it don’t simply understand what is happening, they can intervene while it is in process.

Typical applications are used to protect healthcare institutions from deepfake hackers; enhance voice AI agent’s emotion and empathy capabilities; reduce extremism and harassment on social platforms; observe and monitor voice agent performance; detect and stop child grooming voice conversations; and protect agents in high-risk scenarios from being identified through advanced voice masking.

“Voice is becoming a primary interface for AI, and that creates a whole new set of problems that can’t be solved from a transcript,” explains Carter Huffman, CEO and co-founder at Modulate. “We’re already using audio-native AI to protect organizations from deepfake attacks, help voice agents understand emotion and respond with more empathy, identify dangerous behavior in online conversations, and monitor whether voice agents are actually performing the way they’re supposed to.”

Advertisement. Scroll to continue reading.

The new funding will be used to further develop Modulate’s team and infrastructure, and to expand the models, APIs, SDKs, integrations and deployment options available to the developers and partners that build voice applications; while continuing to invest in its own underlying research and technology.

Written By Kevin Townsend

Source Verification & Original Intelligence

This threat report was reviewed by CyberNew analysts and cross-referenced with primary security disclosures from SecurityWeek.

Primary Advisory →