Product details

Attention Tag enables speakers / teachers on popular conferencing platforms or custom apps get the following benefits:

  1. Real-time insights: The AI runs continuously and derives actionable inferences for the AI assistants to execute, thereby enabling you to intervene in real time and drive engagement.
  2. Automated actions: Speakers can get real time feedback and actionable insights during the course based on AI inferences from attendees’ camera.
  3. Learner feedback: Attendees can get individual, pointed feedback; for example, at the end of a 90 min session, they can be pointed to specific sections of the recording where they seemed confused.
  4. Speaker feedback: Instructors can get feedback to improve their course content, based on aggregated engagement levels of all attendees.

The innovative product (patent filed) is also:

  • Privacy first. Our AI models run on the edge, and no video or images are ever transferred to the servers.
  • Cost efficient. With the models running on the edge, infrastructure requirements are minimal, reducing bandwidth and infra costs
  • Developer-friendly. The AI is packaged into an SDK, easily embeddable on any video-call platform or LMS. The architecture is optimized for scale, a generic data scheme & APIs to consume the data. Custom dashboards can easily be added. 

Integrations & Deployment options

Attention Tag can be integrated into your application through any of the followig mechanisms:

  1. Plugin on popular video conferencing platforms, with our Zoom & Microsoft Teams ready & soon to be published on their marketplaces.
  2. Plugin on popular learning management solutions (LMS), eg like this Moodle plugin already live
  3. Custom video conferencing / edtech / content apps can use our client-side SDK that can easily be integrated into any video conferencing or recorded content platform. It has been used in our in-house developed Zoom & Moodle integrations.
  4. Physical classrooms / conference sites with various hardware configurations are supported as well.

The software stack, data models, and internal workflow engines have been designed for easy functional expansion and scalability. As new AI models are developed or identified, they can be easily added to the SDK, with the backend analytics easily generalizing to handle additional signals.

Demo

Here’s the product visual demo.

Reach out to us for actual demo credentials below.

Interested?

If you are interested in trying the product, demo credentials or integrating, reach out to us on hello@attentiontag.com or fill this form.