Organizations running AI pipelines need current web content. Old snapshots go stale fast. The web data infrastructure company, Decodo, has rolled out a Web Data API. The new product offers teams building agents, retrieval pipelines, and training sets four essential functions under a single key – scraping, search, mapping, and crawling.
Why data pipelines need more than a snapshot
Large language models train on a fixed snapshot of the web. That snapshot stops updating once training ends. Any system that relies on old data makes the same kind of mistake. A price-tracking pipeline built on stale data reports yesterday’s price as current. A news pipeline misses a story that broke an hour ago. A research pipeline cites a company address that changed last year.
Retrieval-augmented generation grounds a model’s answers in documents pulled at query time. If those documents are stale, the grounding fails too. Keeping a pipeline supplied with current pages usually means building scraping infrastructure. That work covers managing proxies, handling CAPTCHAs, and getting past blocks.
Four endpoints under one key
Decodo built the Web Data API on its existing proxy network. It already carries 125M+ ethically sourced residential, ISP, mobile, and datacenter IPs across 195+ locations. The API itself covers four endpoints, each handling a separate stage of data collection. A team can call one endpoint for a page, or chain all four.
- Scrape pulls clean content from a single page, even behind anti-bot protection.
- Search returns live SERP results.
- Map discovers a site’s structure, with up to 147K URLs per call.
- Crawl follows links across a site and pulls up to 10K pages per job.
Vaidotas Juknys, CEO at Decodo, noted, “Analytics teams kept rebuilding the same pipeline every quarter. They would scrape a page, search for updates, then still miss half a site. Map and crawl give them the full picture in one pass. That is what data teams asked us for directly.”
One key, one bill, and fewer moving parts
The pitch is simple – one key now covers scrape, search, map, and crawl, replacing the separate logins, dashboards, and invoices that come with running several vendors at once. Developers get a single place to check usage and a single bill to track, and a finance team reviewing vendor spend sees one line item instead of several. When an engineer needs to debug a failed request, checking one dashboard instead of juggling multiple accounts makes it easier to trace the problem back to its source.
Running scrape, search, map, and crawl through separate vendors also means separate rate limits, error formats, and status pages to track. With one provider, the pipeline needs one set of retry and error-handling logic. When something goes wrong, there’s one status page to check and one support team to contact.
How users can integrate it into their workflows
A RAG team building an internal knowledge base can crawl a vendor’s documentation once a week, with each run refreshing the embeddings that ground the assistant’s answers. A developer working on a coding assistant can call search mid-session for a current answer, which beats asking the model to guess from training data. An analytics team tracking a set of competitors can map their catalogs to catch new and removed products, then crawl the product pages on a regular schedule, turning a manual price check into a recurring job that feeds a dashboard.
A data science team can crawl a set of public sites to build a training corpus. Running map first shows the total volume before a single page is pulled, so the crawl stays focused on pages that belong in the dataset. From refreshing embeddings to feeding a pricing dashboard, every one of these workflows runs on the same key, with no separate scraping stack for each use case.
Getting started, and the build versus buy question
For most developers building data pipelines, unblocking is the hard part. Proxies get banned, CAPTCHAs appear, and anti-bot systems change without warning. Decodo handles all of that behind the scenes, so every request returns real-time, reliable data without the team maintaining any bypass logic themselves.
The Web Data API scales in both directions. A small team can start on the free tier and run a real project without building any scraping infrastructure. A team with large data needs can use the same proxy network and endpoints to run crawls and maps at volume, without switching providers as usage grows.
Testing the Web Data API doesn’t require a credit card. The free tier includes up to 10K requests every month, shared across all four endpoints. That’s more than many APIs include on their free plans. Once a team outgrows the free tier, billing follows the same one-key setup they started with.
