Deepgram Voice AI for government
Mission-ready speech-to-text, text-to-speech, and voice agents, deployable in GovCloud, on premises, or fully air-gapped environments.
Leading voice teams build with Deepgram
Built for the mission you run
Defense, federal civilian, intelligence, and state and local agencies. Each deployed the way its mission actually requires.
On-prem, edge, air-gapped
Models trained for mission audio
Mission audio breaks commercial models—shouting, jamming, code-switching, and mission phraseology. Deepgram's models are domain-adapted for exactly those conditions.
GovCloud and on-prem
The call center gets an upgrade
The VA runs more than 50 million contact-center calls a year on legacy IVR, at 21% caller satisfaction. Deepgram's real-time voice agents and 100% call QA drop into that same stack, so modernization doesn't mean replacement.
On-prem and air-gapped
Deploy inside controlled boundaries
Deepgram's Nova and Flux models run self-hosted with zero egress in classified networks, with the same accuracy and latency you'd test in the cloud, and are backed by In-Q-Tel, an investor since 2021.
Cloud and on-prem
Where the mission meets the public
Agencies serving residents directly run high call volume with small teams. Deepgram handles real-time transcription, translation, and call QA for 311, permitting, benefits, and public safety lines, in the cloud, or on-prem where policy requires it.
Contract vehicles
The paperwork's already done
Deepgram is available on GSA MAS, SEWP VI through Carahsoft, OTA and Tradewinds, and NASPO, so your contracting officer likely already has a path to us, no new vehicle required.
Accuracy, measured against real competitors
Benchmark results for Deepgram speech-to-text, with the same model available in cloud, on-prem, and air-gapped.
- 54.3%Lower word error rate than Whisper
- 7.7xFaster batch transcription than Whisper
- 100 termsKeyterm boosting with no retraining
Accurate, deployable, and audit-ready
Models tuned for mission audio, deployable in the cloud, on-prem, or air-gapped, and compliant with the standards you already review.
In-house foundation models
We build our own speech models, so accuracy improvements ship on our own roadmap.
Keyterm boosting, no retraining
Load up to 100 mission-specific terms per request, including call signs, program names, and acronyms.
Hard audio, domain-adapted
Handles the conditions that break general-purpose models: shouting, jamming, radio artifacts, code-switching, and heavy accents.
Cloud and GovCloud, pilot-ready
Start in GovCloud and pilot on real mission audio within days.
On-prem, zero egress
Run the same models inside your boundary. No audio leaves your network, and no internet dependency.
Air-gapped, fully disconnected
Deploy in classified and disconnected networks, including edge hardware with no outside connectivity.
Your audio stays yours
Government audio only trains our models with your explicit consent, and opt-out is built into the platform, not a contract addendum.
Aligned to OMB M-25-22
Opt-out training is native to the federal AI memo’s requirements, so procurement review starts from a shorter list.
Auditable by design
Full session logging, retention controls, and access boundaries you configure and your security team can review.
FAQ
Yes. The same speech-to-text and text-to-speech models, along with the infrastructure to build and run voice agents, can be deployed self-hosted with zero egress, including on fully disconnected and classified networks. Speech recognition, accuracy, and model latency match what you measure in the cloud because you're running the same models, not reduced edge variants.
GSA MAS, SEWP VI through Carahsoft, OTA and Tradewinds, and NASPO. In most cases your contracting officer already has a path to us without standing up a new vehicle. Separately, Deepgram has been in the In-Q-Tel portfolio since 2021.
No. Government audio never trains our models without consent, and opt-out is native to the platform rather than a contract addendum. This aligns with OMB M-25-22, which shortens the review your privacy and security teams have to run.
In our benchmark testing, Deepgram speech-to-text delivered 54.3% lower word error rate and 7.7x faster batch transcription than Whisper. Mission audio adds shouting, jamming, code-switching, and phraseology, so we recommend measuring on your own recordings during evaluation.
Yes, and that is the path most agencies take. Pilot in GovCloud to prove accuracy on real audio, then deploy the identical models inside your boundary or air-gapped for production. There is no re-integration, because the API surface is the same.
Two things at once. Deepgram's real-time voice agents handle routine calls that legacy IVR routes badly, and 100% call QA replaces sampling. The VA alone reportedly runs more than 50 million calls a year at 21% caller satisfaction, which is the scale of the opportunity.