Meeting Transcript Memory

The agent processes a 45-minute product meeting transcript, extracts 8 key topics (competitor names, technologies, features), searches Google and Reddit for each via Scavio ($0.04 total), and stores enriched summaries. Next time someone asks 'what did we decide about the pricing model,' the agent retrieves the meeting context plus current competitor pricing data.

Meeting Transcript Memory is relevant to Google, YouTube. Scavio provides a unified API to access data from all of these platforms.

Meeting transcripts contain high-value organizational context: decisions made, action items assigned, technical discussions, client requirements, and strategic direction. Feeding this context into AI agent memory transforms agents from generic assistants into context-aware team members. Processing pipeline: (1) Capture -- export transcripts from Zoom, Google Meet, Teams, or Otter.ai as text. (2) Extract -- use an LLM to identify key information: decisions, action items, named entities, technical terms, dates, and commitments. (3) Index -- store extracted information in a vector database or structured format for retrieval. (4) Enrich -- cross-reference extracted entities with web data: if a competitor was discussed, search for their latest news. If a technology was mentioned, find current documentation. The enrichment step is where search APIs add value. After extracting 'the team discussed switching to Rust for the backend,' an agent can automatically search for 'Rust backend migration guide 2026' via Scavio ($0.005/query) and pre-load relevant context for the next related conversation. Privacy considerations: meeting transcripts often contain sensitive information. Processing should happen locally or within trusted infrastructure. The search enrichment layer (calling external APIs with extracted topics) should use general queries, not verbatim transcript content. Cost structure: transcript processing is LLM cost (varies by model and length). Search enrichment adds $0.005 per entity searched. A typical 1-hour meeting produces 5-15 searchable entities = $0.025-$0.075 in search costs.