Deepgram’s Unicorn Leap: Voice AI Raises $130M Series C at $1.3B Valuation

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What happened

Deepgram, a San Francisco–based Voice AI company, announced a $130 million Series C funding round at a $1.3 billion valuation. The round was led by AVP with participation from new investors like Alumni Ventures, Princeville Capital, and Citi Ventures, as well as existing backers including Tiger Global, Madrona, BlackRock, and In‑Q‑Tel. Funds will support global expansion, new model development, strategic acquisitions (including OfOne), and technology scaling.

Who is affected

  • Deepgram’s customers and partners: Over 1,300 organizations across sectors such as retail, healthcare, and fintech use Deepgram’s real‑time speech‑to‑text and voice agent APIs.
  • Voice AI ecosystem: Investors, developers, and enterprise tech teams integrating voice interfaces will see increased competition and innovation.
  • Industry leaders: Notable companies like NASA and Amazon Web Services, which leverage Deepgram tech, may benefit from broader language support and enhanced models.

Why CISOs should care

Voice AI adoption is accelerating across customer service, contact centers, and internal automation. This investment signals that voice interfaces are moving into mainstream enterprise use, raising security and compliance considerations around audio data capture, storage, transcription accuracy, and API integration. The rapid expansion of highly capable voice models increases the attack surface for leakage of sensitive information if not properly governed. Additionally, acquisitions like OfOne expand the use of voice AI into new verticals, amplifying the need for robust security frameworks.

3 practical actions

  1. Assess voice AI risk profiles: Inventory where voice technologies like Deepgram are or could be integrated and identify associated risks (data leakage, PII exposure).
  2. Update security policies: Include voice and speech‑to‑text services in data governance policies, ensuring encryption in transit and at rest, access controls, and clear data retention rules.
  3. Engage engineering teams: Collaborate with developers and platform owners to ensure secure API usage, regular vulnerability testing, and compliance with privacy regulations when deploying or scaling voice interfaces.