Airgram
Turn meetings into actionable insights with AI-powered transcription and automated summaries.
Turn organizational conversations into a searchable, AI-powered corporate memory.
MeetRepository represents the next evolution of meeting intelligence by shifting the focus from simple transcription to long-term knowledge retention. By 2026, it has positioned itself as a critical layer in the 'Corporate Brain' stack, utilizing advanced Large Language Models (LLMs) to not only record and transcribe calls but to semantically index them for cross-meeting insights. The architecture is built on a high-availability ingestion engine that supports Zoom, Microsoft Teams, and Google Meet via bot-based recording and direct file uploads. Unlike standard transcription tools, MeetRepository emphasizes the 'Repository' aspect, offering structured storage where AI identifies recurring themes, tracks project evolution over months of discussions, and provides automated sentiment analysis across entire departments. Its technical framework leverages multi-modal AI to synchronize video frames with transcript timestamps, allowing users to search for visual cues—such as a specific slide deck presented during a call—alongside verbal keywords. For the enterprise, it provides a centralized hub that eliminates information silos, ensuring that institutional knowledge isn't lost when employees churn.
Uses vector embeddings to allow users to search for the 'meaning' of a conversation rather than specific words.
Turn meetings into actionable insights with AI-powered transcription and automated summaries.
Transform long-form video content into actionable technical abstracts and structured knowledge bases.
The world's highest accuracy AI assistant for instantly summarizing videos, lectures, and documents.
Transform meeting noise into actionable intelligence with AI-driven knowledge synthesis.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Aggregates data from multiple recordings to track the progress of a single project or topic over time.
Neural network-based speaker identification that learns voices over time for 98% accuracy.
Computer vision algorithms detect and capture presentation slides shared during meetings, linking them to transcript segments.
Analyzes tone and word choice in real-time to provide a heat-map of meeting engagement and sentiment.
Allows users to ask custom questions of a meeting recording (e.g., 'What were the three main concerns raised by the client?').
Supports transcription and summarization in over 50 languages with automatic language detection.
Account Executives lose critical customer details when passing leads to Customer Success Managers.
Registry Updated:2/7/2026
Valuable user feedback is buried in hours of interview recordings.
Verifying verbal agreements made during long internal or external calls.