Extralt

Extralt is an ecommerce scraping and product data enrichment platform. It extracts product pages from online stores, enriches them into a standard schema, and matches equivalent products across stores for comparison. It is built for teams that need recurring ecommerce data without maintaining their own scraping infrastructure.

Extralt's AI studies a store once, reverse-engineers its product API where one exists, and writes a crawler in Rust that compiles into a native library, so later runs execute as plain code rather than a model call per page. Before shipping, the crawler must extract every required field correctly from 3 live product pages. If a site redesign later breaks the crawler, the run stops and AI rebuilds and revalidates it automatically.

Enrich turns each captured page into an Item with one language, one price format, and a standard taxonomy, classifying products into Shopify's Standard Product Taxonomy with 14,606 categories. Items are then matched into products, variants, listings, and offers across stores, and Explore runs price position, price movement, availability, and assortment-overlap analyses that link every figure back to its source page. Data can be read through the dashboard, an API, SDKs, MCP, or file export.

Extralt's Start plan is free, requires no credit card, and gives 3,000 credits valid for 30 days, covering 3,000 extraction-only pages or 1,500 pages with both extraction and enrichment, one run at a time. Scale runs from $30 to $1,000 a month, with a default of $100 a month for 50,000 credits and extra credits at $2.00 per 1,000. Business, aimed at the lowest price per credit, is coming soon and requires contacting the company.

Use cases

• Comparing prices for the same product across competing stores
• Tracking which listed prices changed between observations
• Detecting stock-outs and restocks across stores
• Finding which product variants overlap between catalogs