Meeting note tools give you a wall of text and a list of action items that live in yet another app. After a meeting, explicitly save the decisions, commitments, and blockers that should survive as typed memory.
You have a 47-minute recording and an AI-generated summary. Somewhere in there, three decisions were made and two people committed to follow-ups. Finding them later means re-reading or re-watching.
3ngram: Ask your AI to identify the structured outcomes, review them, and save the records that matter: decisions as decisions, action items as commitments, and blockers as blockers. Each saved record becomes searchable.
Otter, Granola, Fireflies: your meeting notes live in a separate tool. They don't connect to your project context, your commitments, or your AI's understanding of the work. They're reference material at best.
3ngram: Save selected meeting outcomes into the same account-level memory your MCP clients use. Wednesday's coding session can search Tuesday's decision, and a later briefing can return still-open commitments.
Before a recurring meeting, you check last time's notes, scan your task list, and review recent emails. This takes 10 minutes and you still miss something.
3ngram: Invoke a scoped briefing for open commitments, blockers, and recent decisions, then search for the meeting topic if you need detail. 3ngram does not read your calendar or email in v1.
Illustrative AI-client presentation assembled from explicitly saved memories. 3ngram returns structured, bounded records; it does not ingest external systems or generate this narrative in the background.
No. 3ngram does not record, transcribe, or ingest meetings. Use your preferred transcription tool, paste only the excerpts you choose into an AI conversation, and explicitly save the resulting records.
There is no calendar-aware meeting-prep prompt in v1. Invoke the briefing tool for a scope or project and use search for the meeting topic; your AI client can organize the returned memories into talking points.
Yes. Use those tools for transcription. Then paste key excerpts into your AI conversation and run the post-meeting prompt to extract structured outcomes into 3ngram.
Explicitly turn selected meeting outcomes into typed, persistent memory, then search or brief those records in a later session.