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Train AI models with 100x more data from meetings

Enable thousands of many-to-many conversations stimulated by presented content on Scoot to drive a dramatic increase in contextual data available for AI and LLM initiatives.

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How it works

In a Scoot meeting with 10,000 employees, there are typically 1,000 simultaneous conversations. We gather each conversation in the context of who is saying what to whom, creating high quality transcripts of these conversations with attributions as directed by the meeting host.

For example, after their formal presentation, a CEO can ask attendees (organized in small groups) to discuss the topics presented. Discussions can be on any topic, ranging from “what are our opportunities to grow sales” to “what are the unique aspects of our products that drive customer demand.” We capture the small group conversations and create a rich, extensive source of contextual data for use in a LLM.

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Rich, contextual data is a strategic imperative

AI and LLM initiatives are a top priority for global enterprises because the efficiencies they bring will deliver competitive advantages. While the applications of AI and LLMs are still in the early days, it is clear that both quality and quantity are critically important with respect to training data.

No data is more valuable than that generated by humans who are knowledgeable about a domain (market, products, customer preferences) and the business itself.

Many-to-many vs. one-to-many

Most large virtual meetings in the past have been hosted on webinar platforms, broadcast platforms, or virtual event platforms. These are essentially one-to-many experiences, where content is delivered on an individual basis from a central hub to one person at a time. There is almost no interaction among attendees.

In the age of AI and LLMs, hosting large virtual meetings on one-to-many platforms puts companies at a strategic disadvantage. Orders of magnitude more rich, contextual data can be collected from conversations if a many-to-many platform like Scoot is used instead.

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Privacy and user experience

Recording a large meeting in Scoot works in the same way that it does on any legacy meeting platform. Users are informed that the meeting is being recorded, and a visual indicator is presented in the interface. Hosts have full control over recording capabilities. Nothing is recorded unless the meeting host initiates recording.

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Your data, your choice

Scoot has a range of options available for data collection. Data can be anonymized or associated with imported Smart Badge data, such as title, department, or tenure. Upon entry into your LLM, data can be tagged and weighted based on your objectives and goals. Options are available to collect transcribed text, audio, or full video.

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Use cases

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Host customer events and analyze perceived and actual value.

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Find opportunities hidden beneath hierarchies and power structures.

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Customer Support

Improve language models with a dramatic increase of highly contextual, expert voice data.

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Identify operational inefficiencies, anomalies, and process defects.

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Overlay Smart Badge data with meeting recordings to feed sales AI models and increase rep effectiveness and sales.

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Increase conversion rates and reduce costs with AI generated copy that is enhanced with contextual, enterprise-specific data.

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Expand patent breadth by discovering additional use cases for claims.

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Human Resources

Provide more effective self-serve HR functions and go beyond polls and surveys to understand retention and engagement.

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Learning and development

Grow the corpus of data available for prioritizing programs and creating course materials more efficiently.

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Data architecture and export

Data collection and storage can be fully hosted by Scoot or architected for AWS, Azure, Google, Oracle, or any Custom Data Cloud. We provide you with the API and tools you need to easily export your LLM training datasets to your database of choice or ETL tool.

Don’t just meet. Scoot. 

Try out our innovative virtual meeting platform and ultra-engaging features for yourself.

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