Extralt

What is Extralt?

Extralt is an ecommerce scraping and product data enrichment platform operated by Extralt SAS in France. Its site describes the product as turning "ecommerce pages or your own files into clean, matched product data," so that an agent can handle collection and enrichment while users compare prices, track availability, or build applications with the results. The stated positioning is that there is "no infrastructure to run" and that the resulting data is "connected across stores."

The product is organized around a three-stage pipeline — Extract, Enrich, and Explore — which the company also describes as the three shapes in its logo. The documentation frames the platform as going "beyond ecommerce scraping": users extract public product and catalog pages, enrich the resulting Captures into normalized Items, connect records across stores, and inspect the dataset through the dashboard, API, and MCP.

How Extralt works

Extract. Extralt generates a crawler for each website, validates it on real pages, and runs it when the user chooses. Each product page becomes a Capture: what the page said, its URL, and when it was seen. The documentation lists Robots, Runs, Schedules, and Imports among the platform's operations.

Enrich. Each Capture becomes an Item with clean fields, one price format, and a standard category. Items are then matched across stores into products, variants, listings, and offers, along with their reviews and changes. The site's example shows the brand "NIKE" normalized to "Nike," the size "Taille 42" to "EU 42," the price "134,99 €" to "€134.99," and "En stock" to "In stock."

Explore. Four analyses are offered over collected data: price position, price movements, availability changes, and assortment overlap. The site states that each number links back to the pages it came from. Explore is reachable through dashboard views, API resources, SQL, exports, OAuth-authenticated MCP tools, dashboard AI queries, and a dashboard agent.

An agent workflow sits on top: a user requests collection, the agent prepares a plan (for example, validate crawlers for three stores, extract up to 300 product pages, then enrich and match), shows an estimated credit cost, and the user approves the work.

Main features

• Per-website crawler generation and validation on real pages
• Capture-to-Item normalization: consistent fields, price format, and category
• Cross-store matching into products, variants, listings, and offers, with reviews and changes
• Four analyses: price position, price movements, availability changes, assortment overlap
• Multiple access surfaces: dashboard, API, SQL, exports, MCP tools, dashboard AI queries, and the dashboard agent
• Operations for Robots, Runs, Schedules, Imports, and Enrichments
• Support for ingesting your own files alongside scraped pages

Pricing

Extralt uses usage-based pricing in credits, with two plans listed.

• Start: $29/month, including 10,000 credits, one run at a time, and email support. The site states this covers 10,000 pages for Extract only, or 5,000 pages for Extract + Enrich, depending on where credits are spent.
• Scale 300k: $300/month, including 300,000 credits, unlimited concurrent runs, and priority support. Credit top-up is available at $1.50 per 1,000 credits. This covers 300,000 pages for Extract only, or 150,000 pages for Extract + Enrich.

A 7-day free trial includes 5,000 credits. Extraction costs 1 credit per successfully extracted product URL (one Capture), and enrichment costs 1 credit per successfully enriched Capture (one normalized Item plus analytics data), so a Capture + Enrich flow costs 2 credits. The site states that failed attempts, retries, browser rendering, and crawler maintenance use no credits, and that Explore reads — dashboard, API, SQL, export, and agent queries — are included. Each successful refresh counts again. A worked example: 1,000 pages extracted and enriched produces 1,000 Captures and 1,000 Items and costs 2,000 credits.

Common use cases

The site's sample scenarios include comparing prices for the same product across stores, tracking price changes over time, monitoring availability shifts, and measuring assortment overlap. Because records carry store, price, availability, URL, and observation time, the platform is oriented toward competitive price and catalog monitoring and toward powering applications built on the collected data. Extralt also supports importing your own files, which the site groups with its enrichment workflow.

Limitations

• Coverage is framed around public product and catalog pages; the pages do not describe access to private or authenticated data.
• Extract alone produces Captures rather than normalized Items, so cross-store matching and comparable prices depend on running enrichment.
• Consumption is credit-based and each successful refresh counts again, so recurring collection incurs recurring credit use.
• Only two plans are documented, with unlimited concurrent runs and credit top-up pricing attached to the Scale 300k plan.
• The site's store names, URLs, prices, and observation timestamps are explicitly labeled illustrative, so they are not evidence of coverage of any specific retailer.
• The supplied pages do not state supported geographies, retailer coverage, retention terms, or service-level commitments, so those remain unspecified.

Summary

Extralt is a usage-priced ecommerce scraping and enrichment platform that collects public product pages, normalizes them into a shared data model, matches the same products across stores, and exposes the result through analyses, API, SQL, exports, and agent tooling. Its plans start at $29/month and scale to $300/month, with credits consumed only on successful extraction and enrichment and reads included.