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Deployment Brief

Deepgram: Aura-2

Deepgram: Aura-2 is a usage-based model with non-token support, suited to speech generation and voiceover production for enterprise teams.

Try Deepgram: Aura-2 with your team

Last reviewed: 2026-08-01

Deepgram: Aura-2

Deepgram

Stable
Context Window
N/A
Input
Usage-based
Audio Output
Usage-based

What can you do with Deepgram: Aura-2?

Practical ways teams can use Deepgram: Aura-2 inside governed AI workflows.

01

Create voiceovers with Deepgram: Aura-2

Generate approved narration for product demos, support videos, training clips, and internal updates with Deepgram: Aura-2.

02

Produce audio variants with Deepgram: Aura-2

Create tone, pacing, and language variants for campaign and enablement workflows with Deepgram: Aura-2.

03

Draft podcast segments with Deepgram: Aura-2

Generate short audio scripts, intros, summaries, and narration assets for content teams with Deepgram: Aura-2.

04

Localize spoken content with Deepgram: Aura-2

Adapt approved narration for different audiences, regions, and accessibility needs with Deepgram: Aura-2.

05

Create training narration with Deepgram: Aura-2

Produce consistent voice assets for onboarding, compliance, and internal enablement material with Deepgram: Aura-2.

06

Govern audio generation with Deepgram: Aura-2

Keep generated speech behind approvals, role access, budget controls, and audit logs with Deepgram: Aura-2.

Why this model

Deepgram: Aura-2 is available in Remova as a non-token option with Usage-based input pricing, Usage-based output pricing, and text->speech modality support for enterprise AI operations.

  • Deepgram: Aura-2 offers non-token capacity for enterprise prompts and documents.
  • Current Remova pricing band is usage-based: Usage-based input and Usage-based output.
  • Best-fit workloads include: Speech generation, Voiceover production, Narration workflows.
  • Route requests by policy tier so teams do not overuse capability.

At a glance

Model ID
deepgram/aura-2
Context Window
N/A
Modality
text->speech
Input Modalities
text
Output Modalities
speech
Input Price
Usage-based
Output Price
Usage-based
Provider
Deepgram
Listing Date
2026-07-16

Strengths

  • Deepgram: Aura-2 is suited for speech generation.
  • Supports text->speech workflows for governed media and automation use cases.
  • Pricing profile is usage-based, enabling predictable workload routing decisions.
  • Can be paired with policy guardrails for safer deployment at scale.

Tradeoffs

  • Governance controls are still required for regulated or sensitive workflows.
  • Operational drift can appear over time without recurring quality evaluations.
  • Usage-based media models need per-workflow cost estimates before broad rollout.
  • Speech generation workflows need voice, consent, localization, and review controls.

Best for

  • Deepgram: Aura-2 for spoken responses with brand, policy, and review safeguards.
  • Deepgram: Aura-2 for approved voiceover, narration, and localized speech assets.
  • Deepgram: Aura-2 for narration workflows with brand, voice, and publication review controls.
  • Deepgram: Aura-2 for media teams that need repeatable speech generation under budget limits.

Rollout checklist

  • Define where Deepgram: Aura-2 is default vs. fallback in your routing policy.
  • Enable role-based access and policy checks before opening access broadly.
  • Set spend guardrails by team and monitor weekly token consumption.
  • Define escalation rules to premium models before launch.
  • Re-run quality and cost benchmarks monthly as newer releases appear.

Related models

Explore adjacent model profiles for routing and benchmarking decisions.

Free Resource

Where Should Your Team Start with AI?

Tell us your industry and team size. We'll tell you which AI use cases will save the most time with the least setup.

You get

A shortlist of AI use cases ranked by impact and effort for your situation.

Tuning notes

voice

Use approved voices and consent rules before generating narration or spoken responses.

language

Validate pronunciation, localization, and audience fit for each target language.

retention

Apply retention rules to source text, generated audio, and review records.

review_queue

Route customer-facing audio through brand and policy review before publication.

Free Assessment

What Could Go Wrong?

5 questions about how your company uses AI today. We'll show you the risks most companies miss until it's too late.

You get

A risk breakdown with the 3 things you should fix first.

Book demo
Knowledge Hub

Deepgram: Aura-2 FAQs

Choose Deepgram: Aura-2 when the workload aligns with speech generation, voiceover production, narration workflows and quality targets justify its pricing profile.
It depends on workload mix. Most organizations use routing policies so routine traffic stays on lower-cost tiers.
Validate quality on real internal prompts, token efficiency, latency, and policy compliance behavior.

Deploy This Model With Governance

Use policy controls, role-based access, and budget guardrails before enabling advanced model tiers at scale.

Try Deepgram: Aura-2 with your team