Pick AssemblyAI if you mainly transcribe recorded calls, podcasts or meetings and want speech understanding, guardrails and an LLM gateway on top. Pick Deepgram if you're building real-time voice agents and want speech recognition, speech output and an agent API from one vendor. The two now overlap a lot, so there's no clear winner.
A banner on Deepgram's home page says Daily and Pipecat are joining the company. That's the most useful single fact about this pair right now, because it tells you where the voice AI market is heading: away from selling transcription on its own, and towards owning the whole conversation.
Both are heading for the whole voice pipeline
It's tempting to frame this pair as two speech-to-text APIs. That doesn't hold any more. The voice-agent platform already sells speech recognition, text-to-speech, a Voice Agent API and audio intelligence. Bringing in Daily and Pipecat moves it closer to owning the real-time voice agent stack rather than only the speech models.
The transcription specialist is crossing over too, from the other direction. It's launched what it says is its first text-to-speech model, and it now offers an LLM Gateway and an MCP server for building with AI agents. So both vendors are moving from transcription into the full voice-agent pipeline. The question for you is which one is further along in the part you need first.
Where my advice lands
If most of your audio is recorded, such as sales calls, podcasts and meetings, and you want understanding and guardrail layers on top of the transcript, the transcription specialist is the more natural fit. If you're building a live voice agent or a contact-centre product and want listening, thinking and speaking handled by one vendor, the voice-agent platform is the stronger match. There's a lot of overlap, so a quick look at both with your own audio is sensible before you commit.
Product by product
| Area | AssemblyAI | Deepgram |
|---|---|---|
| Product shape | Separate APIs for pre-recorded, streaming and sync transcription, plus speech understanding and dictation | One platform of STT, TTS, a Voice Agent API and audio intelligence, with STT models named Flux and Nova |
| Text-to-speech | Its first text-to-speech model, newly launched | Flux TTS, described as conversation-native text-to-speech |
| Agent building | An LLM Gateway and an MCP server for AI agents | A Voice Agent API that handles listening, the LLM and speaking, with function calling examples |
| Deployment | Self Hosted Voice AI Cloud on offer | STT in its own cloud, on regional endpoints or self-hosted |
| Languages | Wide language coverage for pre-recorded transcription (vendor claim) | Language switching and code-switching mid-utterance, with a named set of languages |
| Company news | Promoting its new text-to-speech model | Daily and Pipecat joining, per its home page banner |
Recorded audio or live conversation
The transcription specialist splits its offer into separate APIs for pre-recorded, streaming and sync transcription, with speech understanding and dictation alongside. The vendor says it handles a wide range of languages for pre-recorded work and claims low latency for streaming. That makes it a strong candidate if you're processing a library of recorded calls or episodes.
The voice-agent platform leads with conversation. Its Flux model is pitched at conversational speech recognition, it lists Nova as another speech model, and its speech-to-text page highlights language switching and code-switching mid-utterance. If your callers swap languages halfway through a sentence, that's a feature to look at closely.
Speaking back and building agents
Text-to-speech is the newest ground for one of them. The transcription specialist has only just launched its first text-to-speech model. The voice-agent platform offers Flux TTS, which it calls conversation-native, and wraps it inside a Voice Agent API that handles the loop of listening, calling an LLM and speaking, with function calling examples to get you started.
The transcription specialist takes a more modular route to agents, with an LLM Gateway and an MCP server rather than a single agent API. You'd assemble more of the loop yourself. If the voice side matters as much as the listening side, our guide to text-to-speech software and our list of AI voice generators cover the speaking half in more depth.
Where it runs and what it understands
Both offer a way to keep audio off someone else's servers. The transcription specialist lists a Self Hosted Voice AI Cloud. The voice-agent platform says its speech-to-text can run in its own cloud, on regional endpoints or self-hosted. If you work under strict data rules, ask each one what self-hosting includes for the products you plan to use, because it may not cover the whole range.
Questions for your shortlist call
- Is most of our audio recorded, or live? Recorded leans one way, live conversation leans the other.
- Do we need the vendor to speak back, or only to listen? Text-to-speech is brand new on one side.
- Will we build the agent loop ourselves, or do we want an API that handles it?
- Do our callers switch languages mid-sentence?
- Which products does self-hosting cover?
Other speech APIs to put on the list
Speechmatics
Best for: Multilingual speech-to-text for regulated industries and live captioning, with enterprise-grade security the vendor says runs wherever your data lives.
Rev AI
Best for: A speech-to-text API for async and streaming audio, with topic and sentiment APIs alongside, aimed at developers.
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Gladia
Best for: Meeting assistants and contact-centre builders who want real-time and async speech-to-text; it publishes its own comparison pages against this pair.
ElevenLabs Scribe
Best for: Speech-to-text from a vendor best known for voice generation, handy for teams already using ElevenLabs voices.
Do you make a speech-to-text or voice AI API? Tool makers can ask to be considered for a featured place on this page.
Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.
Frequently asked questions
Is AssemblyAI only for transcription?
Not any more. Alongside its transcription APIs it offers speech understanding, guardrails, an LLM Gateway and its first text-to-speech model.
What does the Daily and Pipecat news mean for Deepgram?
Its home page banner says Daily and Pipecat are joining the company, which moves it closer to owning the real-time voice agent stack rather than only the speech models.
Which one is better for live voice agents?
The voice-agent platform has a Voice Agent API that handles listening, the LLM and speaking. The transcription specialist offers an LLM Gateway and an MCP server, so you'd build more of the loop yourself.
Can I self-host either one?
Both mention it. One lists a Self Hosted Voice AI Cloud, the other says its speech-to-text can run self-hosted or on regional endpoints.
Is there a free trial?
The voice-agent platform states a free trial. Check the transcription specialist's sign-up page for what new accounts get.
