Moved

Build Meeting Notes Knowledge Graph from Google Drive — FalkorDB (CocoIndex v1)

Extract structured information from meeting notes stored in Google Drive and build a knowledge graph in FalkorDB. The flow ingests Markdown notes, splits them by headings into per-meeting sections, uses an LLM (via LiteLLM + instructor) to parse participants, organizer, time, and tasks, and writes nodes and relationships into the graph.

Please drop CocoIndex on Github a star to support us and stay tuned for more updates. Thank you so much 🥥🤗.

What this builds

• Meeting nodes — one per meeting section, keyed by a stable integer id derived from (note_file, date)
• Person nodes — canonical organizers, participants, and task assignees, deduplicated by an embedding + LLM entity-resolution pass (so "Alice", "Alice Chen", and "alice c." collapse to a single node)
• Task nodes — tasks decided in meetings (keyed by description)
• Relationships:
  • ATTENDED — Person → Meeting (with is_organizer flag)
  • DECIDED — Meeting → Task
  • ASSIGNED_TO — Person → Task

The source is one or more Google Drive folders shared with a service account. The flow watches for changes and keeps the graph up to date incrementally.

Get Started

• Neo4j version → examples/meeting_notes_graph_neo4j

• FalkorDB version → examples/meeting_notes_graph_falkordb