Run multi-model research analysis and email reports with GPT-4, Claude and NVIDIA NIM
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
Nodes used (11)
- Webhook
n8n-nodes-base.webhook - Edit Fields (Set)
n8n-nodes-base.set - Code
n8n-nodes-base.code - HTTP Request
n8n-nodes-base.httpRequest - Merge
n8n-nodes-base.merge - If
n8n-nodes-base.if - Switch
n8n-nodes-base.switch - Wait
n8n-nodes-base.wait - Postgres
n8n-nodes-base.postgres - Slack
n8n-nodes-base.slack - Send Email
n8n-nodes-base.emailSend
What it does
How It Works This workflow automates end-to-end research analysis by coordinating multiple AI models—including NVIDIA NIM (Llama), OpenAI GPT-4, and Claude to analyze uploaded documents, extract insights, and generate polished reports delivered via email. Built for researchers, academics, and business analysts, it enables fast, accurate synthesis of information from multiple sources. The workflow eliminates the manual burden of document review, cross-referencing, and report compilation by running parallel AI analyses, aggregating and validating model outputs, and producing structured, publication-ready documents in minutes instead of hours. Data flows from Google Sheets (user input) through document extraction, parallel AI processing, response aggregation, quality validation, structured storage in Google Sheets, automated report formatting, and final delivery via Gmail with attachments. Setup Steps 1. Configure API credentials 2. Add OpenAI API key with GPT-4 access enabled 3. Connect Anthropic Claude API credentials 4. Set up Google Sheets integration with read/write permissions 5. Configure Gmail credentials with OAuth2 authentication for automated email 6. Customize email templates and report formatting preferences Prerequisites NVIDIA NIM API access, OpenAI API key (GPT-4 enabled), Anthropic Claude API key Use Cases Academic literature reviews, competitive intelligence reports Customization Adjust AI model parameters (temperature, tokens) per analysis depth needs Benefits Reduces research analysis time by 80%, eliminates single-source bias through multi-model consensus