ElevenLabs launches experimental ElevenAI app for team meeting notes and dictation

In recent months, Fireflies, Wispr Flow, and Granola have all released competing capabilities in the dictation and meeting note-taking space. The newest entrant in that category is voice AI company ElevenLabs, which this week released an experimental app called ElevenAI that combines meeting note-taking, dictation, and agent integration.

Launched during its 11/11 Summit in New York, ElevenAI is still in preview, and users must sign up for early access rather than simply downloading an app. ElevenLabs, valued at $22 billion, is positioning the product as something that lives within a team rather than a productivity tool for an individual.

ElevenAI includes the features typically found in other apps in the category. It can take notes across your meetings and notify other participants that the conversation is being recorded. Users can query data across meetings and get live assistance during a chat, helping them recall a key detail from older conversations. ElevenLabs also lets companies integrate ElevenAgent and take follow-up actions, such as drafting an email based on meeting notes.

There is also a dictation feature that converts speech into cleaned-up text in any app, with support for more than 90 languages. The company said the app can understand industry-specific terms in both dictation and meeting transcription.

ElevenAI lets the company showcase its own model and use its agent platforms to better funnel context. The startup's positioning may not be to compete directly in the productivity market, but rather to give enterprise teams an option to avoid buying licenses for a separate notetaker and use its solution instead. Meeting-related tools are all racing to become central knowledge hubs for companies while aiming to automate knowledge extraction and follow-up actions.

In the past week, the company also launched its v3 series of Scribe speech-to-text models, with live transcription capabilities and the ability for companies to fine-tune models using their own data, a tool to select the right language model based on use case, and a routine creator that automates tasks based on the transcript.