Introduction
Beyond ecommerce scraping. Extract, enrich, and compare product data across stores.
Give Extralt a public product or catalog URL and a country. Extract uses compiled extraction logic built for the website to create structured Captures with the original URL and observation time. Enrich turns each successful Capture into one normalized Item, then connects Products, exact Variants, store Listings, observed Offers, Reviews, and Stores before the Enrichment becomes ready. Explore provides evidence views, four repeatable Analyses, custom questions across the connected model, and the same capabilities through the dashboard Agent.
Who is Extralt for?
Extralt is for technical teams that need reusable ecommerce product data from public sources without building and maintaining a custom scraper for every website:
- Price intelligence -- monitor competitor pricing across the open web
- Catalog enrichment -- fill gaps in your product data with external sources
- Assortment analysis -- compare observed catalogs and exact matched Variants
- Product research -- reuse source evidence, taxonomy, identifiers, and history
What can you do with it?
Extralt's pipeline has three stages.
| Stage | What it does | Status |
|---|---|---|
| Extract | Run managed ecommerce extraction and produce Captures | Available |
| Enrich | Produce one normalized Item per successful Capture and publish its analytical projection | Available |
| Explore | Browse evidence, run four versioned Analyses, and ask custom questions across the connected model | Available |
The pipeline is useful incrementally. Captures can be inspected and exported without Enrich. Items can be queried directly, while an Enrichment remains active until its committed scope is ready for Explore.
How it works
Extralt uses an LLM-based harness to design extraction logic for a website, then compiles and validates that logic before it is used for repeated Runs. Extraction itself runs as compiled code rather than sending every product page to an LLM.
You provide a URL and a country. Extralt either reuses a compatible Robot or creates a Robot and starts its internal build. Once it is completed, create a Run manually, create a recurring Schedule, or ask the dashboard Agent to prepare an approval plan. The Agent can prepare a Robot, Run, Schedule, or Enrichment operation, but it never executes state-changing work without dashboard approval.