The #1 Speech to Text API for medical transcription
Automate clinical notes and doctor-patient dialogues into Electronic Health Records affordably and efficiently with industry-leading Nova-2 medical model.
The medical transcription API developers deserve and trust
Poor transcription accuracy increases administrative burden of clinicians and leads to decreased medical reimbursement due to under-coded medical notes.
Fast and accurate
Generate clinical notes at scale with fast and accurate speech-to-text that captures specific medical terms and jargon.
HIPAA compliant
HIPAA-compliant transcription and self-hosted on-prem deployment protect patient privacy and ensure compliance with PHI regulations.
Workflow automation
Streamline workflows and reduce administrative overhead to allow providers to focus on what matters most for their patients.
Unbeatable value and performance
Deepgram's Nova-2 medical model is built to handle common healthcare terminology (including symptoms, diagnoses, treatments, medications, and clinical jargon), surpassing all competitors in speed, accuracy, and cost.
We offer maximum controllability with versatile options for managed or self-hosted deployments in the cloud and on-prem as well as enterprise-grade security in our models and infrastructure to ensure HIPAA compliance.
Transcripts you can trust
Built-in support for speaker labels (diarization) and word timings enhance readability and streamlining workflows.
Smart formatting features include automatic punctuation and paragraphs, contextualized entities, alphanumerics, proper noun handling, and more.
Fast, actionable insights
Real-time streaming transcription, long audio file handling, and up to 40x faster transcription creation of pre-recorded audio than alternatives.
Voice AI models that can create accurate summaries and identify speaker sentiment, topics and intent enable enhanced analytics and workflow automation.
Benchmark-backed performance
Deepgram's Nova-2 Medical Model leads the market in medical transcription accuracy, outperforming leading alternatives by 42% on average.
Deepgram's speech-to-text has been far and away the best we've seen for medical transcription accuracy. Plus their approach makes it easy to add in new, uncommon words outside of their training domain.
We have been using the Nova-2 medical model for the last months, and have had a very positive experience. Having medical speech recognition with good accuracy makes a significant difference in the notes that doctors create using our AI Scribe. We are impressed with its ability to recognize medical terms and the blazing processing speed of our audio files.