AI-powered stock analysis with AI scoring and Gmail report delivery
Ready for 3.0What this workflow does
This AI workflow has 17 nodes and runs when a chat message arrives. Along the way it connects Supabase Vector Store, Embeddings OpenAI, Reranker Cohere and HTTP Request and 3 more. It also calls apirest.danelfin.com over HTTP.
How it runs
Trigger: When a chat message arrives.
- Danelfin request (AI Agent): runs an AI agent, with model: Set a reasoning model; 5 tools (Think, ranking, sectors, industries…); memory: Postgres Chat Memory
- Markdown: converts between Markdown and HTML
- Send report (Gmail): uses Gmail
- Supabase Vector Store: stores documents in the Supabase vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader
Services it uses
HTTP calls to: apirest.danelfin.com
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 (13)
- Think Tool
@n8n/n8n-nodes-langchain.toolThink - Supabase Vector Store
@n8n/n8n-nodes-langchain.vectorStoreSupabase - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Reranker Cohere
@n8n/n8n-nodes-langchain.rerankerCohere - AI Agent
@n8n/n8n-nodes-langchain.agent - Http Request Tool
n8n-nodes-base.httpRequestTool - Gmail
n8n-nodes-base.gmail - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Postgres Chat Memory
@n8n/n8n-nodes-langchain.memoryPostgresChat - OpenRouter Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenRouter - Markdown
n8n-nodes-base.markdown - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter
From the author
Workflow Description and Setup Guide This workflow provides comprehensive AI-driven stock analysis, generating detailed deep reports by leveraging advanced vector-based data retrieval and API integrations for precise financial analytics using Danelfin scoring…