Scraping the web for leads, pricing, or competitive intel sounds easy in theory. But scaling it, keeping it clean, and routing it somewhere useful is the real challenge. Most teams either spend hours wrangling spreadsheets or abandon the workflow before completing it.

In this article, we’ll cover:

• What Lindy is and who it’s built for

• How Bright Data and Lindy work together for different use cases

• Examples like competitor monitoring, lead enrichment, and market tracking

• How to connect both the platforms

• Tips for making sure your workflow stays useful over time

Let’s begin with Lindy and what it can do.

What is Lindy and who is it for?

Lindy is an automation platform for building AI agents that handle routine work tasks. It can help you with tasks like responding to emails, updating CRMs, scheduling calls, or extracting insights from documents without writing any code.

Small teams, founders, and operators who are juggling too many manual workflows across too many tools can benefit from Lindy. Think of it like hiring a few sharp operations assistants, while not hiring anyone at all.

You configure each agent’s logic visually using a drag-and-drop workflow builder. You choose the inputs, set conditions or actions, and decide how you want the agent to notify or loop you in.

You can also use prebuilt templates to handle common tasks like lead qualification, follow-ups, meeting scheduling, and more.

Here are a few real-world examples:

• A Lindy agent answers an inbound call, logs it in a Google Sheet, and follows up with a scheduling link.

• It can score new leads from a Typeform survey, sort them, and add them to your CRM with tags.

• Lindy helps you scan and triage daily unread emails. It can then categorize them into buckets like billing, scheduling, and priority replies.

Lindy connects with 7,000+ tools and works across your existing stack. It doesn’t require technical setup or scripts, so teams can launch workflows without writing scripts or hiring engineers.

Let’s look at where Lindy and Bright Data can work together for businesses.

When AI agents meet real-time web data: Use-cases that work

Bright Data gives you access to real-time public web data. Lindy lets you automate what happens next. When used together, they can take manual research and routing tasks off your plate entirely.

These tasks can be tracking competitors, working leads, or keeping tabs on market shifts. Here are three ways these tools can work together:

Competitor research

Tracking competitor moves is useful, but doing it manually demands a lot of time. With Bright Data, you can monitor pricing pages, feature changelogs, blog updates, or even reviews across platforms like G2 and Trustpilot.

Once you capture that data, a Lindy agent can take over. It can pull out key updates, summarize what changed, and drop the highlights into a Slack channel or Notion doc, and tag the right person on your team.

This workflow saves your team time by skipping manual link digging and monthly reports. It runs in the background, keeping your team updated as things happen.

Lead list enrichment

Bright Data can collect company-level or contact-level info like job titles, tech stack usage, locations, or recent hiring activity. That data is useful only if you route it to the right place and turn it into action.

That’s where Lindy comes in. As new leads come in, a Lindy agent can clean the entries, enrich them with tags, score them using logic you define, and send them into your CRM. It can also assign the lead to a rep, create a task, or even trigger an outbound email or call.

This setup helps teams stay organized without having to constantly monitor lead spreadsheets or CRM records every week.

Market intelligence reporting

Staying on top of market shifts can be difficult if your team is into SaaS, finance, or e-commerce. Bright Data can monitor everything from job boards and regulatory pages to niche news sites or Reddit threads.

Lindy agents can summarize those updates into digestible reports. You can have an AI agent that sends out a weekly digest on Fridays. You can also create separate agents for product, GTM, and ops teams based on the type of data coming in.

These reports can trigger next steps, like creating a ticket, scheduling a meeting, or notifying the right Slack channel when something needs attention.

Next up, let’s walk through what a simple Bright Data + Lindy flow looks like in practice.

How to connect Bright Data with Lindy

To connect Bright Data with Lindy and run your first flow, start by choosing the data you need from Bright Data and defining how Lindy should act on it.

Bright Data pulls fresh data from the public web, and Lindy acts on that data based on rules you define. Here’s how you set up a basic flow:

Step 1: Create your Bright Data query or dataset

Start by deciding what kind of data you want. Bright Data offers a few ways to do this:

• Use a prebuilt dataset, like ecommerce listings or product reviews

• Create a custom scraping job using their Web Scraper IDE or Web Unlocker

• Pull structured results via API for specific search terms or domains

You can stream the output in real time via webhook, export it to CSV, or sync it to a storage bucket. You can also control the format and frequency, whether it’s hourly updates or a weekly snapshot.

Step 2: Set up a Lindy agent to monitor or act on the data

Build a Lindy agent to process the data once you sort the data feed. Choose a use case, like lead enrichment, reporting, alerts, and set up your logic visually using Lindy’s drag-and-drop builder.

For example:

• If a new competitor update comes in from Bright Data, summarize it and post to Slack.

• When a new job post mentions [X] tech stack, flag it in a Google Sheet.

• If a lead has raised funding in the last 30 days, assign it to our outbound sales development representative (SDR).

Lindy agents can read structured data, extract the useful parts, and generate summaries. They can then take actions like sending messages, updating CRMs, or creating documents.

Step 3: Configure triggers and outputs

Now connect the two tools. You can either:

• Set Bright Data to push data to Lindy via a webhook

• Have Lindy poll a Google Sheet or endpoint where Bright Data drops results

Once data comes in, Lindy can:

• Post summaries to Slack

• Append insights to Notion or Google Docs

• Create tasks in your CRM

• Schedule calls or send follow-up emails

You can preview all outputs before publishing, and add approval steps if needed, helpful for workflows that still require human oversight.

Let’s look at how to continuously generate useful reports and automations with your Bright Data + Lindy setup.

Tips to get the most out of Bright Data + Lindy

The best way to get the most out of Bright Data + Lindy is to start small and build scalable workflows with clear outcomes.

Here are a few ways to do so:

Start with one clear outcome

Don’t try to automate everything at once. Pick one process where you’re already doing manual work, like weekly pricing research, routing scraped leads, or pulling job board updates. Start with one manual workflow and run it end-to-end before adding more.

Use approval steps when needed

Lindy lets you insert manual checkpoints, so you don’t have to hand over full control right away. This is especially useful for outbound messages, client-facing summaries, or workflows that might surface edge cases.

Name your steps and logic clearly

Inside Lindy, label each agent and workflow with what it’s doing. It makes it easier to hand off, edit, or debug your flow later.

Don’t limit Bright Data to scraping

Most people think of Bright Data for price or product scraping. But it’s just as useful for tracking hiring trends, investor activity, sentiment changes in reviews, or even monitoring legislation across government sites.

Schedule reviews of your workflows

Set a monthly reminder to check if your flow is still doing what you need it to do. Ask if the data is still relevant, the logic is still accurate, and the right people are getting the outputs.

It’s easier to justify investing in a few more AI agents once you get value from your first agent setup. Start with something simple, then expand based on what your team needs.

Automate web data workflows with Bright Data and Lindy

You no longer need to copy-paste scraped data into your CRM or turn raw spreadsheets into something usable. Bright Data pulls in live insights from the web and Lindy turns them into summaries, Slack alerts, lead records, or email updates automatically.

Here’s what they can handle:

• Competitor monitoring: Scrape changelogs, pricing pages, or review sites using Bright Data, then have a Lindy agent organize the findings and notify the right people.

• Lead enrichment that updates itself: Use Bright Data to collect fresh contact or firmographic data, and let Lindy score the leads, route them, and kick off outbound steps.

• Market tracking that drives action: Monitor hiring shifts, industry news, or product trends. Use Lindy agents to generate weekly reports, send follow-ups, or even trigger internal workflows based on what changes.

• No technical setup needed: Start with a Lindy template, plug in a Bright Data source, and go from web signal to business outcome in minutes.

You don’t need to automate everything. Start by identifying the workflow that takes up most of your team’s time, and see how pairing Lindy with Bright Data can make your life easier.

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