What Deepgram shipped in 2026

When the docs write the code: migrating my Speech-to-Text playground to Python SDK v6

Deepgram’s v6 Python SDK is fully generated from the API schema, replacing hand-built WebSocket clients and requiring extensive code changes. A Senior Applied Engineer rewrote a customer-facing tool f…

Voice recognition in healthcare: compliance, accuracy, and deployment realities

Deepgram argues benchmark Word Error Rate (WER) overstates clinical voice AI accuracy, highlighting medical-entity error rates and real-world noise as key differentiators. The post details HIPAA compl…

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AI Voice Agent for Benefits Verification: Automating the Eligibility Call

Deepgram introduced an AI voice agent that automates eligibility and benefits verification calls, reducing manual processes that cost $14.32 per transaction. The agent handles both electronic 270/271 …

AI Phone Agent for Patient Intake: What Happens Before the Appointment

Deepgram introduced an AI phone agent designed to automate patient intake workflows, including demographics collection, insurance ID verification, and visit reason documentation. The system relies on …

Automated Patient Reminders: How AI Voice Agents Reduce No-Shows

Deepgram introduced AI voice agents that automate patient reminders, enabling real-time rescheduling, waitlist backfill, and multilingual outreach within the same call. The system integrates with EHRs…

Deepgram Flux adds word-level timestamps in API responses

Deepgram’s Flux model now returns word-level timestamps in its speech-to-text responses, including start and end times for each word in the transcript. The change is additive and backward-compatible, …

Deepgram adds Claude Sonnet 5 to Voice Agent API, deprecates Sonnet 4

Deepgram introduced `claude-sonnet-5` as a managed Anthropic LLM in its Voice Agent API, offering improved reasoning and conversational quality for voice agents. Concurrently, the older `claude-sonnet…

Deepgram Self-Hosted June 2026 release adds Flux word-level timestamps and model metadata changes

Deepgram’s June 2026 self-hosted release (260630) introduces Flux word-level timestamps, fixes Spanish number formatting, expands number/currency formatting, and improves streaming timestamp accuracy.…

Changelog | Product Enhancements

Deepgram integrates STT/TTS with Amazon Connect and Lex

Deepgram now supports integration with Amazon Connect and Amazon Lex, allowing organizations to replace AWS Transcribe and Polly with Deepgram's STT and TTS models without altering existing Connect fl…

Introducing Deepgram’s Voice Agent API

Deepgram introduced the Voice Agent API, a unified voice-to-voice API enabling enterprises to build LLM-powered AI agents for customer support and order taking. The API leverages industry-leading spee…

Radiology speech recognition: dictation accuracy for diagnostic workflows

Deepgram introduced Nova-3 Medical, a radiology-specific speech-to-text API addressing up to 22% error rates in general-purpose models. Nova-3 Medical achieves a 6.79% keyword error rate by handling d…

What Is Automatic Speech Recognition and How Does It Work?

Deepgram’s product marketing team published a comprehensive guide on automatic speech recognition (ASR) in 2026, detailing four model architectures (streaming conformers, encoder-decoder transformers,…

Top APIs for Building Programmable Voice Agents: What the Stack Looks Like in Production

Your misbehaving agent is likely an audio quality problem

Deepgram argues that misbehaving voice agents typically result from poor audio quality rather than model or prompt flaws. Background noise causes transcription errors and false interruptions, while ha…

Restaurants stack every audio quality problem at once, and Deepgram is fixing it

Deepgram addresses restaurant-specific audio challenges by introducing primary speaker identification in its speech-to-text model, using rolling enrollment windows to distinguish the customer’s voice …

Conversational intelligence for enterprise sales: CRM pipelines, coaching, and revenue attribution

Deepgram’s blog post argues that conversation intelligence (CI) for sales teams fails unless the underlying speech-to-text (STT) layer delivers high accuracy on entity extraction (names, companies, co…