🎬 Generate research proposals with GPT-4o, web search, and quality control agents
⚡ 466 views · 🎬 Content Creation & Video
Description
How It Works
This workflow automates academic and professional research proposal generation using a multi-agent AI pipeline. It targets researchers, academics, grant writers, and R&D teams who need structured, high-quality proposals efficiently. The core problem it solves: manually drafting proposals is time-consuming, inconsistent, and prone to missing key elements like ethics, impact, and funding alignment. A Supervisor Agent orchestrates three specialist sub-agents, Research Content, Strategic Planning, and Ethics/Impact, each powered by dedicated AI models. A Funding Agency Research Tool and Web Search Tool supply real-time context. The generated proposal is parsed, then evaluated by a Quality Control Agent. Proposals meeting the quality threshold are formatted and stored; those falling short are flagged for human revision, ensuring only polished outputs reach storage.
Setup Steps
- Add OpenAI (or compatible) API credentials to all AI model nodes.
- Configure Supervisor, Research Content, Strategic Planning, and QC Agent system prompts.
- Set up Funding Agency Research Tool with target agency endpoints or search parameters.
- Connect Web Search Tool credentials (e.g., SerpAPI or Tavily).
- Configure storage node (Google Sheets/database) with target schema.
- Set quality score threshold in the Check Quality Score node.
Prerequisites
- Web search API key (SerpAPI/Tavily)
- Google Sheets or database credentials
Use Cases
- Grant proposal drafting for research institutions
Customisation
- Swap AI models per agent for cost/performance balance
Benefits
- Cuts proposal drafting time by 70–80%
🔗 Nodes Used
AI Agent, OpenAI Chat Model, Simple Memory, Structured Output Parser, SerpApi (Google Search), AI Agent Tool
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File