# AI Research Intelligence Agent (`blank_butter/ai-research-intelligence-agent`) Actor

Autonomous AI agent that researches any topic across the web, integrates multi-source data, and generates structured intelligence reports with sources, key findings, opportunities, and recommendations. Powered by CrewAI + Apify Actors.

- **URL**: https://apify.com/blank\_butter/ai-research-intelligence-agent.md
- **Developed by:** [AI Developer](https://apify.com/blank_butter) (community)
- **Categories:** AI
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).


# README

## AI Research Intelligence Agent

> **One query → comprehensive intelligence report.** Automated deep research powered by CrewAI + LLM, running on the Apify platform.

### What It Does

This Actor turns any research question into a structured, actionable intelligence report. Instead of spending hours searching, reading, and synthesizing, you get:

- **Executive Summary** — TL;DR with key takeaways
- **Key Findings** — Data points, trends, and facts
- **Market Landscape** — Competitors, players, positioning
- **Opportunities** — Actionable gaps and openings
- **Risks** — Threats, regulations, headwinds
- **Recommendations** — Clear next steps
- **Sources** — Every claim backed by a URL

### Perfect For

- 🏢 **Market Research** — Size a market, map competitors, find trends
- 💼 **Due Diligence** — Evaluate a company, technology, or investment
- 📊 **Competitive Intelligence** — Track what rivals are doing
- 📰 **News Monitoring** — Deep-dive into breaking stories
- 🎓 **Academic Research** — Literature review and synthesis
- 🚀 **Product Research** — Validate ideas before building

### How It Works (3-Step Pipeline)

````

1. SEARCH   → Google Search Scraper finds the most relevant sources
2. CRAWL    → Website Content Crawler extracts full text from top pages
3. ANALYZE  → CrewAI agent reads, synthesizes, and writes the report

````

### Input Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| `query` | string | ✅ | — | Your research question (e.g., "AI chip market 2025") |
| `modelName` | string | ❌ | `gpt-4o-mini` | LLM model: `gpt-4o` (best quality) or `gpt-4o-mini` (faster/cheaper) |
| `depth` | string | ❌ | `standard` | Research depth: `quick` (light), `standard` (balanced), `deep` (comprehensive) |
| `maxSources` | integer | ❌ | `10` | Max sources to analyze (3–30) |
| `outputFormat` | string | ❌ | `structured` | Output format: `structured` (JSON) or `markdown` (formatted text) |

### Pricing (Pay Per Event)

| Event | Price | When Charged |
|-------|-------|--------------|
| Actor Start | **$0.15** | Every run (initialization + search) |
| Quick Research | **$0.40** | When depth = `quick` (5 results, 3 pages) |
| Standard Research | **$0.60** | When depth = `standard` (10 results, 7 pages) |
| Deep Research | **$0.90** | When depth = `deep` (20 results, 15 pages) |

**Example costs:**
- Quick fact-check: $0.55 (start + quick)
- Market snapshot: $0.75 (start + standard)
- Due diligence memo: $1.05 (start + deep)

### Output Example

```json
{
  "query": "AI chip market 2025",
  "depth": "deep",
  "model_used": "gpt-4o",
  "tokens_used": 4852,
  "report": {
    "executive_summary": "The AI chip market is projected to reach $200B by 2025...",
    "key_findings": [...],
    "market_landscape": [...],
    "opportunities": [...],
    "risks": [...],
    "recommendations": [...],
    "sources": [...]
  }
}
````

### Architecture

- **Framework:** [CrewAI](https://crewai.com) — multi-agent orchestration
- **Search:** [Google Search Scraper](https://apify.com/apify/google-search-scraper) — SERP extraction
- **Crawl:** [Website Content Crawler](https://apify.com/apify/website-content-crawler) — page text extraction
- **LLM:** OpenAI GPT-4o / GPT-4o-mini
- **Platform:** [Apify](https://apify.com) — serverless execution + monetization

### Development

```bash
## Clone and setup
git clone https://github.com/YOUR_USERNAME/ai-research-intelligence-agent.git
cd ai-research-intelligence-agent

## Install dependencies
pip install -r requirements.txt

## Run locally (requires APIFY_TOKEN env var)
APIFY_TOKEN=your_token_here python -m my_actor
```

### License

MIT — open source, free to fork and improve.

***

**Built with ❤️ by a solo developer using AI. Earn passive income on the [Apify Store](https://apify.com/store).**

# Actor input Schema

## `query` (type: `string`):

The topic, company, market, or question you want researched. Be specific for best results. Examples: 'electric vehicle market China 2026', 'competitor analysis of Notion vs Obsidian', 'AI coding tools market trends'.

## `modelName` (type: `string`):

The OpenAI model used for analysis. GPT-4o gives deeper analysis; GPT-4o-mini is faster and cheaper.

## `depth` (type: `string`):

Controls how many sources are searched and analyzed. Quick = 5 results + 3 pages; Standard = 10 results + 7 pages; Deep = 20 results + 15 pages.

## `maxSources` (type: `integer`):

Maximum number of distinct sources to include in the final report.

## `outputFormat` (type: `string`):

Structured = JSON only; Markdown = JSON + formatted Markdown report.

## Actor input object example

```json
{
  "query": "AI agent economy market size and key players 2026",
  "modelName": "gpt-4o-mini",
  "depth": "standard",
  "maxSources": 10,
  "outputFormat": "structured"
}
```

# Actor output Schema

## `query` (type: `string`):

The original research query submitted by the user.

## `depth` (type: `string`):

Research depth level used: quick, standard, or deep.

## `model_used` (type: `string`):

LLM model used for analysis.

## `tokens_used` (type: `string`):

Total LLM tokens consumed during the research run.

## `report` (type: `string`):

Structured intelligence report containing executive\_summary, key\_findings, market\_landscape, opportunities, risks, recommendations, sources, and raw\_analysis.

## `markdown_report` (type: `string`):

Formatted Markdown version of the report (only present when outputFormat=markdown).

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "AI agent economy market size and key players 2026",
    "modelName": "gpt-4o-mini",
    "depth": "standard",
    "maxSources": 10,
    "outputFormat": "structured"
};

// Run the Actor and wait for it to finish
const run = await client.actor("blank_butter/ai-research-intelligence-agent").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "query": "AI agent economy market size and key players 2026",
    "modelName": "gpt-4o-mini",
    "depth": "standard",
    "maxSources": 10,
    "outputFormat": "structured",
}

# Run the Actor and wait for it to finish
run = client.actor("blank_butter/ai-research-intelligence-agent").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "AI agent economy market size and key players 2026",
  "modelName": "gpt-4o-mini",
  "depth": "standard",
  "maxSources": 10,
  "outputFormat": "structured"
}' |
apify call blank_butter/ai-research-intelligence-agent --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=blank_butter/ai-research-intelligence-agent",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "AI Research Intelligence Agent",
        "description": "Autonomous AI agent that researches any topic across the web, integrates multi-source data, and generates structured intelligence reports with sources, key findings, opportunities, and recommendations. Powered by CrewAI + Apify Actors.",
        "version": "0.1",
        "x-build-id": "UniNIQEm5mdfCJEMX"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/blank_butter~ai-research-intelligence-agent/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-blank_butter-ai-research-intelligence-agent",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/blank_butter~ai-research-intelligence-agent/runs": {
            "post": {
                "operationId": "runs-sync-blank_butter-ai-research-intelligence-agent",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/blank_butter~ai-research-intelligence-agent/run-sync": {
            "post": {
                "operationId": "run-sync-blank_butter-ai-research-intelligence-agent",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "required": [
                    "query"
                ],
                "properties": {
                    "query": {
                        "title": "Research Topic",
                        "type": "string",
                        "description": "The topic, company, market, or question you want researched. Be specific for best results. Examples: 'electric vehicle market China 2026', 'competitor analysis of Notion vs Obsidian', 'AI coding tools market trends'.",
                        "default": "AI agent economy market size and key players 2026"
                    },
                    "modelName": {
                        "title": "LLM Model",
                        "enum": [
                            "gpt-4o",
                            "gpt-4o-mini"
                        ],
                        "type": "string",
                        "description": "The OpenAI model used for analysis. GPT-4o gives deeper analysis; GPT-4o-mini is faster and cheaper.",
                        "default": "gpt-4o-mini"
                    },
                    "depth": {
                        "title": "Research Depth",
                        "enum": [
                            "quick",
                            "standard",
                            "deep"
                        ],
                        "type": "string",
                        "description": "Controls how many sources are searched and analyzed. Quick = 5 results + 3 pages; Standard = 10 results + 7 pages; Deep = 20 results + 15 pages.",
                        "default": "standard"
                    },
                    "maxSources": {
                        "title": "Max Sources to Cite",
                        "minimum": 3,
                        "maximum": 30,
                        "type": "integer",
                        "description": "Maximum number of distinct sources to include in the final report.",
                        "default": 10
                    },
                    "outputFormat": {
                        "title": "Output Format",
                        "enum": [
                            "structured",
                            "markdown"
                        ],
                        "type": "string",
                        "description": "Structured = JSON only; Markdown = JSON + formatted Markdown report.",
                        "default": "structured"
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```