Turn conversations into intelligence
Turn conversational audio into useful insight with fast, purpose-built models that surface summaries, sentiment, intent, and key topics.
Leading voice teams build with Deepgram
Transcripts are just the start
Audio Intelligence runs on lightweight, task-specific models fine-tuned on conversational data. It’s more accurate than general-purpose LLMs, faster, and cost-efficient, without sacrificing latency.
Turn talk into structured signal
A set of features that extracts summaries extract summaries, sentiment, intent, and topics from every conversation.
Conversation summary
Summarization
Turn long conversations into a few accurate sentences, so teams can catch up on a call without listening to the whole recording.
View docs: Summarization
Positive, neutral, negative
Sentiment analysis
Score sentiment at the word, sentence, and transcript level to track trends and improve customer experience in real time.
View docs: Sentiment analysis
Speaker intent
Intent recognition
Track intent across a conversation so agents and applications can act on what a caller wants, not just what they say.
View docs: Intent recognition
Conversation topics
Topic detection
Tag every conversation by topic automatically, so routing, categorization, and trend reports don't need a manual pass.
View docs: Topic detection
Related articles
Deepgram
Introducing new Audio Intelligence models for sentiment, intent, and topic detection
Announcements
Deepgram
Speech-to-text sentiment analysis: Building production-grade voice infrastructure
Deepgram
Named entity recognition for voice: Extracting structure from transcripts
AI Engineering & Research
Deepgram
Ambient intelligence in healthcare: What the technology stack actually looks like
AI Engineering & Research
FAQs
Deepgram Audio Intelligence is a set of features that extract summaries, sentiment, intent, and topics from conversational audio, available as parameters on the Deepgram transcription API. It layers understanding on top of transcription, so applications can act on what was said, not just what words were spoken.
Deepgram Audio Intelligence runs on lightweight, task-specific models fine-tuned on conversational data. Compared to general-purpose LLMs, that typically means higher accuracy on specialized tasks, faster inference, and lower cost per call — which makes high-throughput, low-latency applications viable.
Deepgram Audio Intelligence includes summarization, sentiment analysis, intent recognition, and topic detection. Each is available as a parameter on the Deepgram API and can be combined with transcription in the same request.
Sign up for a free Deepgram account, grab an API key, and add the relevant Audio Intelligence parameters to your transcription request. The Deepgram Playground lets you try each feature against sample or uploaded audio without writing code.