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Not according to the deployment documentation cited here. Deepgram documents self-hosted voice AI and an air-gapped Amazon SageMaker deployment, but does not establish a supported product that runs inference directly on an air-gapped laptop. A file stored on your laptop can still be sent to Deepgram’s hosted API for processing; that is not offline transcription.

What “air-gapped” means for Deepgram

An air-gapped system is isolated from external networks. The key question is where speech recognition actually runs—not where the audio file is stored or which application submits it.

Deepgram’s self-hosting guide describes several customer-infrastructure deployments and says its Amazon SageMaker deployment runs fully air-gapped: “the container is network-isolated and makes no connection to the Deepgram Cloud.” This is an AWS deployment, not evidence of a laptop installation. Deepgram’s self-hosting documentation

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Deepgram also describes on-premises and other self-hosted deployment options, including cloud infrastructure, bare metal, Docker, Podman, and Kubernetes. Those descriptions support an organizational infrastructure use case, but do not specify that the software can be installed or run on an individual laptop. Deepgram’s self-hosted product page

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How the available options differ

Option Where processing happens What it means for an air-gapped laptop
Hosted Deepgram API Deepgram’s hosted service receives API requests. Not offline laptop inference. The API example can read a local audio file and submit it using a Deepgram API key. Pre-recorded audio guide
Docker/Podman or Kubernetes self-hosting Deepgram components run on customer infrastructure. May be relevant to an isolated organizational environment, but Deepgram does not describe this as a laptop product. Its guide says these self-hosted paths require an Enterprise Plan. Self-hosting documentation
Amazon SageMaker A Deepgram container runs as a SageMaker endpoint in AWS. Deepgram describes this deployment as network-isolated with no connection to Deepgram Cloud. It is an AWS endpoint, not an air-gapped laptop. The guide lists an AWS account and applicable SageMaker and AWS Marketplace permissions as requirements. Self-hosting documentation
SDK or CLI Developer tools make it easier to use Deepgram products and APIs. Installing a tool locally does not show that model inference or audio processing happens locally. The JavaScript SDK describes connections to Deepgram-hosted endpoints. Pre-recorded audio guide · JavaScript SDK repository

Why a local audio file is not local transcription

An application can open a file from the laptop’s disk and then upload or stream its contents to a remote service. Deepgram’s pre-recorded-audio example uses a local file with an API key to make an API request. In that workflow, the file starts locally, but processing still uses Deepgram’s API. Deepgram’s pre-recorded audio guide

To establish offline inference, you would need confirmation that the model runs within the laptop’s boundary and that audio, transcripts, licensing checks, and operational telemetry do not cross it. The cited product and developer materials do not establish a laptop-ready offline inference product or give minimum laptop CPU, GPU, or memory specifications.

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What to verify before choosing an isolated deployment

If you are evaluating Deepgram for a secure enclave or other disconnected environment, confirm the details for the exact architecture and contract. Deepgram’s documentation distinguishes SageMaker’s network-isolated behavior from its container deployments: the container documentation describes components contacting a license server to validate components and models and report usage information. Do not assume every self-hosted configuration has the same connectivity behavior as SageMaker. Deepgram’s self-hosting documentation

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  • Inference location: Identify exactly which machine or service processes the audio.
  • Data boundary: Confirm whether audio, transcripts, logs, or other operational data leave the intended environment.
  • Licensing and usage reporting: Establish whether the selected deployment needs connectivity and how it operates when isolated.
  • Infrastructure and support: Confirm who provides and secures the environment, along with contract and support requirements.
  • Compute sizing: Ask Deepgram for requirements for the specific deployment; the cited pages do not provide laptop specifications. Deepgram’s guide directs customers to an account representative for compute planning.

Deepgram’s government page also describes deployment in GovCloud, on-premises, or fully air-gapped environments. That is evidence of organizational deployment options, not proof of a laptop installation. Deepgram government solutions

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