Jamie sees 3x faster pipeline with Scribe

Jamie is an AI assistant for meetings that generates summaries and delivers key insights. The team built a custom LLM pipeline to summarize conversations, extract action items, and highlight decisions.

To get accurate transcripts, they tested all major Speech-to-Text (STT) providers — but none met their standards for transcription and speaker diarization. They ended up building their own pipeline, combining open-source models for diarization and others for transcription. Maintaining it required heavy engineering effort.

That changed with the launch of ElevenLabs Scribe. Jamie tested it immediately, and the results were clear: Scribe handled overlapping speech, interruptions, and non-verbal audio events better than other models. Integration took just a few days, with minimal customizations needed. By switching to Scribe, Jamie significantly reduced engineering overhead while improving transcription quality.

Faster, More Accurate Transcripts — with Less Work

The change had an immediate business impact. Complaints about speaker errors disappeared. Transcription speed tripled — a one-hour meeting is now processed in 30–45 seconds. This helped users reach their “aha” moment faster, which increased both activation and the number of meetings recorded per user.

Scribe also delivered these results across languages including English, German, Spanish, and Dutch.

"Upgrading to Scribe significantly improved our product quality. The ability to accurately capture nuanced conversation dynamics, even in challenging audio environments, has directly translated to more satisfied customers and better meeting insights."
— Egor Spirin, Head of Product & Engineering, meetjamie.ai

Scribe Delivers Accuracy and Speed Out of the Box

Scribe is the first model to combine high transcription and diarization accuracy — right out of the box — at a competitive price. Jamie no longer needs to maintain a complex pipeline. With Scribe, they’ve streamlined operations and improved the product experience for every user.