Turn Meeting Notes into Searchable Knowledge

What you’ll build

A meeting knowledge board that turns raw transcripts into structured, searchable artifacts so decisions never get lost.

Add meeting transcripts as notepad nodes
Vectorize for semantic search
Ask AI to extract decisions, action items, and risks
Create structured sticky notes linked to source meetings
Build a weekly digest across multiple meetings

Prerequisites

ChatGrid API key (get one here)
Node.js 18+ or Python 3.10+
Meeting transcripts (from Otter.ai, Fireflies, Google Meet, or manual notes)

Step 1: Create a meetings board

curl -X POST https://api.chatgrid.ai/v1/boards \
  -H "Authorization: Bearer cgk_live_..." \
  -H "Content-Type: application/json" \
  -d '{"name": "Engineering Meetings — March 2026"}'

const res = await fetch("https://api.chatgrid.ai/v1/boards", {
  method: "POST",
  headers: { Authorization: "Bearer cgk_live_...", "Content-Type": "application/json" },
  body: JSON.stringify({ name: "Engineering Meetings — March 2026" }),
});
const { data: board } = await res.json();
const boardId = board.id;

import requests
API_KEY = "cgk_live_..."
BASE = "https://api.chatgrid.ai/v1"
headers = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}
res = requests.post(f"{BASE}/boards", headers=headers, json={"name": "Engineering Meetings — March 2026"})
board_id = res.json()["data"]["id"]

Step 2: Add a meeting transcript

Create a notepad node with the full transcript text.

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/nodes \
  -H "Authorization: Bearer cgk_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "type": "document",
    "position": {"x": 0, "y": 0},
    "data": {
      "label": "Sprint Planning — March 17",
      "content": "Attendees: Sarah, James, Priya\n\nSarah: We need to decide on the caching layer. Redis vs Valkey.\nJames: Redis has better docs but Valkey is OSS and compatible. I vote Valkey.\nPriya: Agreed. Let'\''s set a deadline — end of sprint.\n\nDecision: Use Valkey for caching. Migration deadline: March 28.\n\nSarah: On API rate limiting — we'\''re seeing 429s from Pro plan customers.\nJames: Bump Pro from 100 to 200 req/min. Action item for me.\nPriya: Also add a retry-after header.\n\nAction items:\n- James: Bump Pro rate limit to 200 req/min\n- Priya: Add retry-after header to 429 responses\n- Sarah: Write ADR for Valkey decision"
    }
  }'

transcript = "Attendees: Sarah, James, Priya\n\nDecision: Use Valkey for caching..."  # full text
node = requests.post(f"{BASE}/boards/{board_id}/nodes", headers=headers, json={
    "type": "document", "position": {"x": 0, "y": 0},
    "data": {"label": "Sprint Planning — March 17", "content": transcript},
})
node_id = node.json()["data"]["id"]

Step 3: Vectorize the transcript

cURL

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/documents/vectorize \
  -H "Authorization: Bearer cgk_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "content": "...(full transcript text)...",
    "node_id": "{nodeId}",
    "metadata": {"source": "sprint-planning", "date": "2026-03-17", "attendees": "Sarah, James, Priya"}
  }'

Step 4: Ask AI to extract decisions and action items

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/chats \
  -H "Authorization: Bearer cgk_live_..." \
  -H "Content-Type: application/json" \
  -d '{"title": "Meeting Extraction"}'

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/chats/{chatId}/messages \
  -H "Authorization: Bearer cgk_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "content": "From the meeting notes on this board, extract: 1) All decisions (with rationale), 2) All action items (with owner and deadline), 3) Any open risks. Format each as a separate item.",
    "stream": false
  }'

const chatRes = await fetch(`https://api.chatgrid.ai/v1/boards/${boardId}/chats`, {
  method: "POST",
  headers: { Authorization: "Bearer cgk_live_...", "Content-Type": "application/json" },
  body: JSON.stringify({ title: "Meeting Extraction" }),
});
const { data: chat } = await chatRes.json();

const msgRes = await fetch(
  `https://api.chatgrid.ai/v1/boards/${boardId}/chats/${chat.id}/messages`,
  {
    method: "POST",
    headers: { Authorization: "Bearer cgk_live_...", "Content-Type": "application/json" },
    body: JSON.stringify({
      content: "From the meeting notes on this board, extract: 1) All decisions (with rationale), 2) All action items (with owner and deadline), 3) Any open risks.",
      stream: false,
    }),
  }
);
const { data: extraction } = await msgRes.json();

Step 5: Create structured sticky notes

Batch-create a sticky note for each extracted item and link them to the source meeting.

cURL

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/nodes/batch \
  -H "Authorization: Bearer cgk_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "operations": [
      {"action": "create", "data": {"type": "note", "position": {"x": 0, "y": 400}, "data": {"label": "Decision", "text": "Use Valkey for caching. Rationale: OSS, Redis-compatible, no license risk. Deadline: March 28."}}},
      {"action": "create", "data": {"type": "note", "position": {"x": 400, "y": 400}, "data": {"label": "Action: James", "text": "Bump Pro rate limit from 100 to 200 req/min."}}},
      {"action": "create", "data": {"type": "note", "position": {"x": 800, "y": 400}, "data": {"label": "Action: Priya", "text": "Add retry-after header to all 429 responses."}}},
      {"action": "create", "data": {"type": "note", "position": {"x": 400, "y": 600}, "data": {"label": "Action: Sarah", "text": "Write ADR for Valkey caching decision."}}}
    ]
  }'

Connect each item back to its source meeting:

cURL

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/edges \
  -H "Authorization: Bearer cgk_live_..." \
  -H "Content-Type: application/json" \
  -d '{"source_node_id": "{decisionNodeId}", "target_node_id": "{meetingNodeId}", "data": {"label": "decided in"}}'

Step 6: Build a weekly digest

After adding multiple meetings, ask AI to produce a digest across all of them.

cURL

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/chats/{chatId}/messages \
  -H "Authorization: Bearer cgk_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "content": "Generate a weekly digest of all meetings on this board. Group by: decisions made, action items with owners, and open risks. Keep it under 300 words.",
    "stream": false
  }'

Search past meetings for specific topics at any time:

cURL

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/documents/search \
  -H "Authorization: Bearer cgk_live_..." \
  -H "Content-Type: application/json" \
  -d '{"query": "when did we decide on the caching layer?", "limit": 3}'

What’s happening under the hood

Meeting transcripts are chunked and embedded like any other document. By tagging each transcript with date and attendees in the metadata, search results carry full provenance. When AI extracts decisions and action items, it performs semantic search across all meeting chunks then reasons over the matches. The sticky notes you create are regular nodes — you can vectorize them too, making decisions searchable independently of the raw transcript. Edges between sticky notes and meeting nodes create a traceable graph: every decision links back to the meeting where it was made.

Cookbooks

Turn Meeting Notes into Searchable Knowledge

What you’ll build

Prerequisites

Step 1: Create a meetings board

Step 2: Add a meeting transcript

Step 3: Vectorize the transcript

Step 4: Ask AI to extract decisions and action items

Step 5: Create structured sticky notes

Step 6: Build a weekly digest

What’s happening under the hood

Next steps

Document Synthesis

Team Knowledge

​What you’ll build

​Prerequisites

​Step 1: Create a meetings board

​Step 2: Add a meeting transcript

​Step 3: Vectorize the transcript

​Step 4: Ask AI to extract decisions and action items

​Step 5: Create structured sticky notes

​Step 6: Build a weekly digest

​What’s happening under the hood

​Next steps

Document Synthesis

Team Knowledge

What you’ll build

Prerequisites

Step 1: Create a meetings board

Step 2: Add a meeting transcript

Step 3: Vectorize the transcript

Step 4: Ask AI to extract decisions and action items

Step 5: Create structured sticky notes

Step 6: Build a weekly digest

What’s happening under the hood

Next steps