Deep Research

Action ID: research_deep_research

Description

Research a topic using a deep research agent.

Connection

Name	Description	Required	Category
OpenAI Connection	The OpenAI connection to call OpenAI API.	True	openai

Input Parameters

Name	Type	Required	Default	Description
topic	string	✓	-	The topic to research.

View JSON Schema

{
  "description": "Deep Research node input.",
  "properties": {
    "topic": {
      "description": "The topic to research.",
      "title": "Topic",
      "type": "string"
    }
  },
  "required": [
    "topic"
  ],
  "title": "DeepResearchInput",
  "type": "object"
}

Output Parameters

Name	Type	Description
data	object	The research data containing comprehensive findings.

View JSON Schema

{
  "description": "Deep Research node output.",
  "properties": {
    "data": {
      "additionalProperties": true,
      "description": "The research data.",
      "title": "Research Data",
      "type": "object"
    }
  },
  "required": [
    "data"
  ],
  "title": "DeepResearchOutput",
  "type": "object"
}

How It Works

This node leverages an AI-powered deep research agent that conducts comprehensive research on your specified topic. The agent formulates research questions, searches multiple sources, synthesizes information, and generates a structured report with findings, insights, and relevant data points. It uses OpenAI's capabilities to analyze, summarize, and organize information from various perspectives.

Usage Examples

Example 1: Technology Research

Input:

topic: "The impact of quantum computing on cryptography"

Output:

data: {
  "summary": "Quantum computing poses significant threats to current cryptographic systems...",
  "key_findings": [
    "RSA and ECC encryption vulnerable to Shor's algorithm",
    "Post-quantum cryptography standards being developed by NIST",
    "Timeline: 10-15 years before quantum computers threaten current encryption"
  ],
  "sources": [...],
  "recommendations": "Organizations should begin planning quantum-resistant strategies..."
}

Example 2: Market Research

Input:

topic: "Electric vehicle market trends in Europe 2024"

Output:

data: {
  "summary": "The European EV market shows strong growth with 25% year-over-year increase...",
  "key_findings": [
    "Norway leads with 87% EV market share",
    "Battery costs decreased 40% since 2020",
    "Government incentives driving adoption"
  ],
  "market_size": "2.3 million units sold in 2024",
  "growth_projections": {...}
}

Example 3: Academic Research

Input:

topic: "Recent advances in CRISPR gene editing technology"

Output:

data: {
  "summary": "CRISPR technology has advanced significantly with new base editing capabilities...",
  "key_findings": [
    "Prime editing allows precise DNA modifications",
    "Clinical trials show promise for sickle cell disease",
    "Ethical considerations remain paramount"
  ],
  "publications": [...],
  "future_directions": "Expanded applications in agriculture and medicine..."
}

Common Use Cases

• Market Analysis: Research industry trends, competitor analysis, and market opportunities

• Academic Research: Gather information on scientific topics, literature reviews, and research summaries

• Business Intelligence: Investigate companies, technologies, or business strategies

• Policy Research: Analyze policy implications, regulatory landscapes, and compliance requirements

• Technology Assessment: Evaluate emerging technologies, their capabilities, and potential impacts

• Competitive Intelligence: Research competitors, their products, and market positioning

• Trend Analysis: Identify and analyze trends in various domains like fashion, technology, or consumer behavior

Error Handling

Error Type	Cause	Solution
Authentication Error	Invalid or missing OpenAI API key	Verify your OpenAI connection is properly configured with a valid API key
Empty Topic	Topic parameter is empty or null	Provide a clear, specific research topic
Rate Limit Error	Too many API requests in a short period	Implement delays between requests or upgrade your OpenAI plan
Timeout Error	Research taking too long to complete	Simplify the topic or break it into smaller research questions
Insufficient Context	Topic is too vague or broad	Provide more specific research parameters and constraints
API Error	OpenAI service issues	Check OpenAI status page and retry after a brief delay

Notes

• Topic Specificity: Provide clear, specific topics for better research results. Vague topics may produce generic findings.

• Research Depth: The agent conducts multi-step research, which may take longer than simple API calls. Allow sufficient time for completion.

• Data Quality: Results depend on the information available and the AI model's training data. Always verify critical information.

• Token Usage: Deep research consumes significant tokens due to multiple API calls. Monitor your OpenAI usage and costs.

• Structured Output: The data object contains structured findings that can be easily parsed and used in subsequent workflow nodes.

• Source Verification: While the agent synthesizes information, always cross-reference important findings with original sources when possible.

• Cost Optimization: Use deep research for complex topics that require comprehensive analysis. For simple questions, consider using standard AI nodes instead.