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TODAY’S DAILY DOSE OF DATA SCIENCE
​[Hands-on] Build a Multi-agent Brand Monitoring System​
Today, we're building a brand monitoring app that scrapes web mentions of a brand at scale and produces insights about a company.
Tech stack:
- ​Bright Data​ to scrape data at scale.
- CrewAI for orchestration.
- ollama to serve DeepSeek-R1 locally.
Here's the workflow:

- Use ​Bright Data​ to scrape brand mentions across X, Instagram, YouTube, websites, etc.
- Invoke platform-specific Crews to analyze the data and generate insights.
- Merge all insights to get the final report.
Let's implement this!
Scraping tool
To monitor a brand, we must scrape data across various sources—X, YouTube, Instagram, websites, etc.
Thus, we'll first gather recent search results from Bright Data's SERP API.

Platform-specific scraping function
The above output will contain links to web pages, X posts, YouTube videos, Instagram posts, etc.
To scrape those sources, we use Bright Data's platform-specific scrapers.

Set up DeepSeek R1 locally
We'll serve R1 locally through Ollama.
To do this:

- First, we download it locally.
- Next, we define it with the CrewAI's LLM class.
Here's the code👇
Crew Setup
We will have multiple Crews, one for each platform (X, Instagram, YouTube, etc.)

Each Crew will have two Agents:
- Analysis Agent → It analyses the scraped content.
- Writer Agent → It produces insights from the analysis.
Below, let's implement the X Crew!
Note: The implementation for other Crews is available in the GitHub repo linked later.
X Analyst Agent
This Agent analyzes the posts scraped by Bright Data and extracts key insights. It is also assigned a task to do so.

X Writer Agent
The Agent takes the output of the X analyst agent and generates insights.

Create a Flow
Finally, we use CrewAI Flows to orchestrate the workflow:

- We start the Flow by using the Scraping tool.
- Next, we invoke platform-specific scrapers.
- Finally, we invoke platform-specific Crews.
We wrap the app in a clear streamlit interface for interactivity and run the Flow.

When Agents use tools, they run into issues like IP blocks, bot traffic, captcha solvers, etc. This hinders the Agent's execution.
​Grab the API_KEY here →​
It lets you:

- Scrape data for Agents at scale without getting blocked.
- Simulate user behavior using advanced browser tools.
- Build Agentic apps with real-time and historical web data.
Thanks to Bright Data for working with us on this demo.
Find the code in this GitHub repo: ​Brand monitoring repo​.
Thanks for reading!
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