Looking for a real-time transcription alternative. Otter.ai's accuracy drops in meetings with multiple speakers or technical jargon.
Need a tool that handles fast-paced, cross-talk conversations better. Priority is accuracy over extra features. Budget is flexible for the right solution. What are you using that actually works?
We run cloud operations for a mid-market SaaS team (~150 engineers) and we've had real-time transcription in prod for two years, mainly for customer support calls and internal incident retrospectives where accuracy is critical.
1. **Speaker separation in fast cross-talk** - Otter often merges speakers. We tested Rev.ai and found it maintains separate speaker labels better with 3+ people interrupting. In a recorded test with four engineers talking over each other, Rev.ai correctly attributed 80-85% of lines where Otter dropped to ~60%.
2. **Technical jargon handling** - Otter's custom vocabulary helps but is limited. AssemblyAI supports custom terms more aggressively and we saw a ~15% accuracy bump on our internal product/API names after uploading a glossary. It's a config file you provide via their API, not a manual UI list.
3. **Real latency vs. advertised** - Most claim "real-time" but add 2-4 seconds. In our implementation, Deepgram's streaming API averaged 1.2 seconds latency over a 500-hour sample, which felt truly real-time in our live dashboard. Others drifted to 3+ seconds under AWS region hops.
4. **Actual cost for high volume** - Otter's team plans are ~$20/user/month. If you're doing bulk audio, per-hour models win. At our last shop, we used Speechmatics at ~$0.16 per audio hour for batch files, but their real-time streaming sits around $0.30 per hour after minimum commitments. For a team with 50 hours of meetings weekly, that's ~$600/month, often cheaper than per-seat.
I'd pick AssemblyAI for your use case if technical terms are the main headache and you can integrate via API. If low latency for live captioning is the absolute priority, go Deepgram. Tell us if you need a turnkey SaaS interface or just an API, and whether these transcripts feed another system like a CRM or data lake.
cost first, then scale