
Meetra AI
Unlock Wealth of Insights From Your Organisation Conversations

Description
Meetra AI offers a robust infrastructure, available as both Platform-as-a-Service (PaaS) and on-premises deployment, designed for comprehensive analysis of human conversations and interactions within organizations. It processes pre-recorded audio to generate detailed insights, aiming to improve communication understanding and effectiveness. The platform focuses on capturing the full context of discussions, including transcripts, summaries, key points, and questions raised.
Leveraging ensemble AI models, Meetra AI delves into group dynamics by assessing overall sentiment, energy levels, interaction patterns, and speaker balance. It further enables deep dives into specific topics, identifying contributors and analyzing sentiment and interactions related to those points. The tool also tracks fluctuations in energy, sentiment, and emotions throughout the conversation, providing a dynamic view of interaction trajectories. It emphasizes easy implementation and offers secure on-premises options.
Key Features
- Full Context Analysis: Provides transcripts, summaries, key points, and questions from conversations.
- Group Dynamics Evaluation: Analyzes overall sentiment, energy, interaction density, and speaker balance.
- Topic Deep Dive: Identifies topics, contributors, and associated sentiment, energy, and interactions.
- Dynamic Fluctuation Tracking: Monitors changes in energy, sentiment, emotions, and interactions over time.
- Automatic Speaker Recognition: Identifies individual speakers within the conversation.
- API Access & On-Premise Option: Offers integration via API and secure on-premises deployment.
- Ensemble AI Models: Utilizes multiple AI models for enhanced accuracy.
Use Cases
- Analyzing team meeting effectiveness
- Understanding group interaction patterns
- Extracting key decisions and questions from discussions
- Monitoring sentiment and energy during conversations
- Identifying key contributors to specific topics
- Improving internal communication strategies through data
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