# 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. |

<details>

<summary>View JSON Schema</summary>

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

</details>

## Output Parameters

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

<details>

<summary>View JSON Schema</summary>

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

</details>

## 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.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.agenticflow.ai/reference/nodes/research_deep_research.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.