AssemblyAI
Speech AI API with best-in-class transcription, speaker diarization, sentiment analysis, and LeMUR LLM-over-audio.
AssemblyAI is the leading speech AI API for developers, offering state-of-the-art speech-to-text alongside a full audio intelligence suite. The Universal-2 transcription model delivers best-in-class accuracy across accents and audio quality. Beyond transcription, AssemblyAI provides auto chapters, speaker diarization, sentiment analysis, topic detection, PII redaction, and content safety moderation - all as simple API calls. LeMUR (Language Model Unified API for Recall) applies LLM reasoning directly over audio files - enabling developers to ask questions, summarize, and extract structured data from recorded conversations without first transcribing manually. Used by Spotify, Salesforce, and 100K+ developers.
Key Features
- Universal-2 transcription model - best-in-class accuracy across accents and low-quality audio
- Speaker diarization - automatically labels who said what in multi-speaker recordings
- LeMUR - apply LLM reasoning (Q&A, summaries, extraction) directly over audio files
- Auto chapters - segment long recordings into titled, timestamped chapters automatically
- Sentiment analysis and topic detection per utterance
- PII redaction - remove sensitive information from transcripts automatically
- Real-time streaming transcription with sub-500ms latency
Use Cases
- Developers adding transcription to meeting recorders, note-taking apps, and voice assistants
- Call center analytics teams extracting insights from customer service recordings at scale
- Podcast and media platforms generating auto-captions and searchable transcripts
- Healthcare companies transcribing clinical dictation with PII redaction
- Sales teams building call intelligence tools to analyze rep performance
- EdTech platforms creating searchable transcripts and chapter navigation for lectures
Pros
- LeMUR enables LLM-powered Q&A and summarization over audio without manual transcript handling
- Best accuracy on challenging audio - accented speech, background noise, and telephony-quality recordings
- Generous free tier (100 hours/month) lets developers prototype without payment
Cons
- More expensive than open-source Whisper for high-volume deployments at $0.37/hour
- LeMUR adds cost on top of transcription - combined pricing escalates for complex pipelines
- No consumer-facing product - API only, requires developer integration
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