# AI Finance Monitoring Agent (`louisdeconinck/ai-finance-monitoring-agent`) Actor

A powerful AI-driven financial research and monitoring tool. This agent automatically generates comprehensive financial analysis reports for publicly traded companies by aggregating data from multiple sources and using AI to synthesize insights.

- **URL**: https://apify.com/louisdeconinck/ai-finance-monitoring-agent.md
- **Developed by:** [Louis Deconinck](https://apify.com/louisdeconinck) (community)
- **Categories:** AI, Agents, Automation
- **Stats:** 12 total users, 0 monthly users, 0.0% runs succeeded, 3 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $100.00 / 1,000 actor starts

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

A powerful AI-driven financial research and monitoring tool built on the Apify platform. This agent automatically generates comprehensive financial analysis reports for publicly traded companies by aggregating data from multiple sources and using AI to synthesize insights.

### Overview

The AI Finance Monitoring Agent collects data from various financial and business intelligence sources to create detailed financial analysis reports for any publicly traded company. It leverages AI to transform raw financial data into actionable investment insights, comparative market analysis, and performance evaluations.

### Features

- **Automated Financial Research**: Generate comprehensive market reports for any publicly traded company using just the ticker symbol
- **Multi-Source Data Aggregation**: Collects and synthesizes data from:
  - Yahoo Finance (stock prices, market metrics, financial ratios)
  - LinkedIn company profiles (company information, employee count, specialties)
  - Crunchbase (funding information, investors, business details)
  - Sector-specific index data for comparative analysis
  - S\&P 500 benchmark data
- **Comparative Market Analysis**: Automatically compares company performance against sector indices and the S\&P 500
- **AI-Powered Report Generation**: Uses Google's Gemini 2.0 Flash model to synthesize collected data into readable, insightful reports
- **Historical Analysis**: Analyze performance over customizable timeframes (1-365 days)
- **Exportable Results**: Reports generated in Markdown format for easy integration into research workflows

### Input

| Parameter | Type | Description | Default |
|-----------|------|-------------|---------|
| `company_ticker` | String | Stock ticker symbol of the company to analyze | Required |
| `past_days` | Integer | Number of past days to analyze (1-365) | 7 |

Example input:

```json
{
  "company_ticker": "AAPL",
  "past_days": 30
}
```

### How It Works

1. **Data Collection**: The agent collects financial data from Yahoo Finance, LinkedIn, and Crunchbase for the specified company
2. **Index Analysis**: Retrieves relevant sector index data and S\&P 500 data for comparative analysis
3. **AI Processing**: Utilizes Gemini 2.0 Flash to analyze the collected data and generate insights
4. **Report Generation**: Creates a detailed markdown report with financial analysis, market trends, and comparative performance
5. **Storage**: Saves the report to the Apify key-value store and pushes structured data to the dataset

### Output Format

The agent produces two outputs:

1. **Markdown Report**: A comprehensive financial analysis report saved in the key-value store
2. **Structured Data**: A JSON object with all collected and analyzed data pushed to the dataset

### Dependencies

- `apify` & `apify-client`: For integration with the Apify platform
- `pydantic-ai`: For AI model integration and structured data handling
- `python-dotenv`: For environment variable management
- `pydantic`: For data validation and settings management

### License

This project is licensed under the MIT License.

# Actor input Schema

## `company_ticker` (type: `string`):

Company ticker symbol.

## `past_days` (type: `integer`):

Select past days to research

## Actor input object example

```json
{
  "company_ticker": "AAPL",
  "past_days": 7
}
```

# 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 = {
    "company_ticker": "AAPL",
    "past_days": 7
};

// Run the Actor and wait for it to finish
const run = await client.actor("louisdeconinck/ai-finance-monitoring-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 = {
    "company_ticker": "AAPL",
    "past_days": 7,
}

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

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

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

```

## CLI example

```bash
echo '{
  "company_ticker": "AAPL",
  "past_days": 7
}' |
apify call louisdeconinck/ai-finance-monitoring-agent --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,louisdeconinck/ai-finance-monitoring-agent"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/7NURqC16blXSB4kT5/builds/ch4kd8Sg3Nbg75T2B/openapi.json