Automate meeting intelligence with VEXA, OpenAI & Mem0 for conversation insights
Ready for 3.0What this workflow does
This AI workflow has 22 nodes and runs when an HTTP POST request hits its webhook URL (plus 2 other triggers). Along the way it connects Redis, Baserow and OpenAI Chat Model. It also calls gateway.dev.vexa.ai and api.mem0.ai over HTTP.
How it runs
Trigger: When an HTTP POST request hits its webhook URL (plus 2 other triggers).
- Route: Bot Action (Start/Stop) (Switch): routes items into 2 branches
- SET your webhook (HTTP Request): calls gateway.dev.vexa.ai (PUT)
- VEXA: Get Transcript (HTTP Request): calls an HTTP API
- Redis: get
- HTTP: Start VEXA Bot (HTTP Request): calls gateway.dev.vexa.ai (POST)
- HTTP: Stop VEXA Bot (HTTP Request): calls an HTTP API (DELETE)
- Process: Split Transcript Segments (Split Out): splits a list into separate items
- Stop and Error: stops the run with an error
- Merge: merges the data from its input branches
- Baserow: update
…plus 7 more steps. See the full node list below.
Services it uses
HTTP calls to: gateway.dev.vexa.ai, api.mem0.ai
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (15)
- No Operation, do nothing
n8n-nodes-base.noOp - Redis
n8n-nodes-base.redis - Webhook
n8n-nodes-base.webhook - Baserow
n8n-nodes-base.baserow - HTTP Request
n8n-nodes-base.httpRequest - Switch
n8n-nodes-base.switch - Split Out
n8n-nodes-base.splitOut - Edit Fields (Set)
n8n-nodes-base.set - Merge
n8n-nodes-base.merge - Aggregate
n8n-nodes-base.aggregate - Information Extractor
@n8n/n8n-nodes-langchain.informationExtractor - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Stop and Error
n8n-nodes-base.stopAndError - Manual Trigger
n8n-nodes-base.manualTrigger - Code
n8n-nodes-base.code
From the author
VEXA: AI-Powered Meeting Intelligence I'll be honest, I built this because I was getting lazy in meetings and missing key details. I started with a simple VEXA integration for transcripts, then added AI to pull out summaries and tasks. But that just solved…