Collect and connect data from the online stores you choose. Work with consistent product details, availability, and offer history to build applications and analyze the catalogs you follow.
Sample observation: 7 Sep 2026, 09:00 UTC. Store names, URLs, and prices are illustrative.
Need fresh data?Your agent prepares collection and enrichment. You approve the work.
Example request
“Collect up to 100 product pages from each of these three stores in France, then enrich the results.”
Plan for your review
01 · Validate crawlers for the three stores.
02 · Extract up to 300 product pages.
03 · Enrich and match the collected products.
Up to 900 credits. Only successful results are charged.
Put data to work
Dashboard & AI
Analyze and compare
API & SQL
Query and integrate
JSON & Parquet
Export extracted data
Your toolsPlanned
Destination connectors
How it comes together
Build your dataset. Choose what comes next.
Start with the stores your work depends on. Collect their records, give them a shared structure, then use the data in Extralt or your own application.
01
Extract
Get the records. Skip the scraping project.
Choose a store and market. Extralt builds, validates, and runs the crawler. Your team gets structured product records without maintaining the scraping infrastructure.
Feed your application.
Use records in your application or export JSON and Parquet. Collect fresh snapshots with their source and observation time preserved.
You now have records from each store. Next, give them a shared structure.
02
Enrich
Different stores. A shared product model.
Store titles and formats vary. Enrich standardizes the details and connects matching products and variants across stores, while preserving each store’s offers.
Add stores without remapping every catalog.
Work with consistent attributes across your stores. Group products by brand or category and compare matching models, colors, and sizes.
Store offers stay separate. Original records stay available.
Your records now share a structure. Use them together to explore the catalogs you collect.
03
Explore
Follow changes. Find the evidence.
Explore the dataset you’ve built. Find gaps in the catalogs you follow, investigate availability, and compare offers for matching products. Collect again to see what changed.
Trace answers to the original observations.
Use the dashboard or ask the agent, then inspect the observations behind each result. Bring the data into your own tools through the API and SQL.
Charged only when a product page is successfully extracted.
Enrich
+1 credit / product page
Charged only when a product page is successfully enriched.
Explore
Included
Compare prices, availability, and assortments in your enriched dataset. Queries use no credits.
Extract + Enrich costs 3 credits per successfully extracted and enriched product page. Failed attempts, crawler generation, browser rendering, retries, and maintenance use no credits.
Start
For your first recurring product dataset.
$29/month
7-day free trial with 5,000 credits included
10,000 credits
1 run at a time
Email support
What this covers each month
Extract only
5,000pages
Extract + Enrich
3,333pages
Up to these amounts when all credits go to either workflow. Each successful refresh counts again.
Scale 300k
For more stores, larger catalogs, and parallel collection.
$300/month
300,000 credits
Unlimited concurrent runs
Priority support
Credit top-up available ($1.50/1,000 credits)
What this covers each month
Extract only
150,000pages
Extract + Enrich
100,000pages
Up to these amounts when all credits go to either workflow. Each successful refresh counts again.
A concrete example
1,000 pages, extracted and enriched
Explore and query the resulting dataset at no additional credit cost.
3,000 credits
2,000 Extract + 1,000 Enrich
Frequently asked questionsFAQ
Start with the ecommerce pages you need
Add a public product or catalog URL and choose its market. Extralt handles the extraction and gives you structured product data you can enrich, compare, and reuse.