Lovable is an AI-powered app builder that turns natural language descriptions into working web applications. When combined with Browse AI, you can turn your scraped data into live dashboards, comparison tools, internal apps, and customer-facing pages without writing code yourself.
This guide covers how to take data from Browse AI and build interactive applications in Lovable, from simple data viewers to full-featured tools your team or customers can use.
📖 This guide focuses on building visual applications from your scraped data. For processing and analyzing data with AI models, see our guide to using Browse AI data with AI assistants.
What you can build
App type | Example |
Price comparison dashboard | Scrape competitor pricing, build a live dashboard that shows price changes over time |
Market research tool | Scrape industry listings, create a searchable/filterable directory |
Job board aggregator | Scrape job postings from multiple sites, build a unified search interface |
Competitor feature tracker | Monitor competitor pages, display a side-by-side feature comparison |
Lead list viewer | Scrape directories or listings, build a CRM-style interface for your sales team |
Content monitoring hub | Track changes across multiple sites, display a timeline of detected updates |
How it works
The workflow has three parts:
Browse AI extracts the data from websites (one-time or on a recurring schedule via monitors).
You feed the data into Lovable (by pasting sample data or connecting the Browse AI API).
Lovable builds the app based on your description and the data structure.
Method 1: Static app from exported data
The simplest approach. Export your data from Browse AI, then use it to build an app in Lovable.
Step 1: Export your data
Go to your robot in Browse AI and click Tables.
Click Export and download as JSON.
Open the JSON file and copy the contents.
Step 2: Describe your app in Lovable
Go to lovable.dev and start a new project.
Describe the app you want to build, including a sample of your data. For example:
Build a product comparison dashboard with the following features: - A searchable, sortable table showing all products - Filter by category and price range - Click a row to see full product details in a side panel - A chart showing price distribution across categories - Clean, modern design with a dark mode toggleHere's a sample of my data (JSON): [paste a few rows of your Browse AI export here]
Lovable will generate a working app based on your description and data structure.
Iterate on the design by describing changes in natural language: "make the table sortable by price," "add a bar chart comparing categories," "change the color scheme to blue."
✅ Tip: Include 3-5 sample rows from your data in the prompt. This gives Lovable the exact field names and data types to work with, so the app matches your data structure from the start.
Method 2: Live app connected to Browse AI API
For apps that need to display fresh data, connect Lovable directly to Browse AI's API. The app fetches the latest scraped data every time it loads.
Step 1: Get your Browse AI API credentials
Go to your Browse AI account settings.
Copy your API key.
Note your robot ID (visible in the URL when you open a robot:
browse.ai/robots/YOUR_ROBOT_ID).
Step 2: Ask Lovable to connect to the API
Describe an app that fetches data from Browse AI's API:
Build a live competitor monitoring dashboard that fetches data from the Browse AI API.API details: - Endpoint: https://api.browse.ai/v2/robots/ROBOT_ID/tasks - Auth header: Authorization: Bearer YOUR_API_KEY - The response contains task results in result.robotTasks.items[] - Each task has capturedTexts (key-value pairs) and capturedLists.items[] (table rows)Features: - Fetch the latest 10 task results on page load - Display the data in a clean table with sorting and filtering - Show when each task was completed (finishedAt field) - Add a "Refresh" button to pull the latest data - Show a loading spinner while fetchingHere's a sample of what the API returns for capturedTexts: [paste a sample response]
Step 3: Secure your API key
⚠️ Important: Never hardcode API keys in a client-side app that's publicly accessible. If your Lovable app is for internal use only, you can use environment variables in Lovable's settings. For public-facing apps, set up a simple backend proxy (Lovable can help you build one with Supabase Edge Functions) that keeps your Browse AI API key on the server.
Method 3: Webhook-powered real-time app
For apps that update in real time as Browse AI scrapes new data. This approach uses a database (like Supabase) as a middle layer.
How it works
Browse AI sends webhook events to a serverless function when a task completes.
The function writes the data to a Supabase database.
Your Lovable app reads from Supabase (with real-time subscriptions for live updates).
Step 1: Set up Supabase
Create a project at supabase.com (free tier available).
Create a table to store your scraped data. Ask Lovable to generate the SQL based on your data shape:
I need a Supabase table to store this Browse AI data: [paste sample of your capturedTexts or capturedLists]Create the SQL to make a table with appropriate columns and types.
Step 2: Create a webhook receiver
Ask Lovable to create a Supabase Edge Function that receives Browse AI webhooks and inserts data:
Create a Supabase Edge Function that: 1. Receives POST requests from Browse AI webhooks 2. Parses the task data from the webhook payload 3. Inserts or updates rows in my scraped_data table 4. Only processes "taskFinishedSuccessfully" events
Step 3: Configure the webhook in Browse AI
Open your robot in Browse AI and go to Integrations.
Add a webhook pointing to your Supabase Edge Function URL.
Select Task finished successfully (and optionally Task captured data changed for monitors).
Step 4: Build the app with real-time data
Ask Lovable to build your app connected to Supabase:
Build a monitoring dashboard that connects to my Supabase project.- Read data from the "scraped_data" table - Use Supabase real-time subscriptions so new data appears without refreshing - Show a timeline of when data was captured - Highlight rows where data changed compared to the previous scrape - Include charts showing trends over time
✅ Tip: Lovable has built-in Supabase integration. You can connect your Supabase project directly from Lovable's settings, and it will handle authentication and real-time subscriptions automatically.
Prompt tips for Lovable
Getting a great app from Lovable starts with a good prompt. Here's what works well for Browse AI data:
Tip | Example |
Include sample data | Paste 3-5 rows of your actual Browse AI JSON so Lovable knows your field names and types |
Describe the user | "This is for our sales team to quickly find competitor pricing" guides design decisions |
Specify interactions | "Clicking a row opens a detail panel" is better than "make it interactive" |
Mention visualizations | "Add a bar chart of prices by category" gets you charts. Vague requests may not. |
Iterate in conversation | Start simple, then add features: "Now add a date range filter" or "Make the table exportable to CSV" |
Example: Building a competitor price tracker
Here's a complete example of going from Browse AI data to a working Lovable app:
1. Set up Browse AI: Create a robot that scrapes competitor product pages, capturing product name, price, category, and URL. Set up a monitor to run daily.
2. Export sample data: Run the robot once and export the results as JSON.
3. Prompt Lovable:
Build a competitor price tracking app with:1. A main dashboard showing: - Total products tracked (count) - Average price with trend arrow - Number of price changes in the last 7 days2. A sortable/filterable product table with columns: - Product name (linked to source URL) - Current price - Previous price (with green/red indicator for changes) - Category - Last updated3. A price history chart for any selected product4. Filter controls: category dropdown, price range slider, "changed recently" toggle5. Clean, professional design. Use a card-based layout.Sample data from my Browse AI export: [paste JSON sample]
4. Connect live data: Once the app looks right with sample data, ask Lovable to connect it to Browse AI's API or set up the Supabase real-time pipeline.
5. Deploy and share: Lovable gives you a shareable URL you can send to your team, or you can deploy to a custom domain.
Next steps
Enrich before you display: Use Claude to add AI-generated fields (categories, summaries, scores) to your data before building the app. See our enrichment guide.
Automate the pipeline: Set up monitors and webhooks so your app always has fresh data. See our automation guide.
Browse AI API: See the full Browse AI API documentation for all available endpoints.
Lovable documentation: Learn more about Lovable's capabilities at docs.lovable.dev.