Olostep

Turn web pages into structured data your AI apps can actually use

30 views ↓ 3.9% MoM · 7.4K users/Feb 2026

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Turn web pages into structured data your AI apps can actually use. Olostep gives you a unified API that scrapes, crawls, and extracts information from websites while handling the messy parts like JavaScript rendering and residential IP rotation.

The core toolkit covers most web data needs. Scraping pulls content with full JS rendering. Crawling grabs every page on a site. Parsers convert unstructured HTML into clean JSON or markdown. there is also an agents feature that automates web research based on prompts you give it. The batches API processes up to 100k URLs in roughly 5-7 minutes, which matters if you're feeding training data into models or running large-scale research operations.

Browser automations handle clicks and form fills. Web monitoring tracks DOM changes, stock availability, price shifts, and job postings. The deep search feature claims hyper-specialized B2B indexes, though the documentation doesn't detail which industries or data types. You can output in markdown, JSON, HTML, or screenshots. Distributed infrastructure runs on VM sandboxes. There's also an MCP Server, which suggests integration potential with broader workflows.

Does it actually work reliably? The free tier includes JavaScript rendering and residential IPs, which is unusual. Most competitors charge extra for those. But rate limits on the free plan are low, so you'll hit walls quickly if you're testing at scale. Credits expire after six months, which could burn you if you prepay and do not use them fast enough. No mention of uptime guarantees or what happens when a scrape fails midway through a batch.

The distributed sandbox setup sounds solid for avoiding IP bans, but there's no transparency around success rates or retry logic. If you're scraping sites with aggressive bot detection, you're flying blind on whether this handles Cloudflare or DataDome effectively. The concurrent request limits vary by tier, but nothing explains throttling behavior or queue management.

They claim to be the most cost-effective option. Let's check. Free plan gives you 500 successful requests. The $9 Starter plan includes 5000 requests monthly with 150 concurrent requests, which works out to $1.80 per 1K requests. Standard is $99 for 200K requests and 500 concurrent, dropping to $0.495 per 1K. Scale hits $399 for 1 million requests at $0.399 per 1K and adds browser automations. Credit packs start at $20 for 10k credits, up to $1000 for 2M credits. Enterprise pricing is custom. The per-request cost does drop substantially as you scale, and the free tier's feature set beats many competitors who gate JS rendering behind paid plans.

Python and Node.js SDKs exist, and google Sheets integration is listed but not detailed. No mobile app or browser extension.

Who actually benefits here? Developers building AI research agents or applications that need continuous web data feeds. If you're training models on web content or automating competitive intelligence, the batch processing speed matters. Companies running price monitoring or inventory tracking across hundreds of sites fit the monitoring features. The agents functionality works for teams building autonomous research tools that need to gather information based on natural language prompts. Not ideal if you need guaranteed uptime SLAs or transparent retry policies. The six-month credit expiration makes prepaying risky unless you have predictable volume.

Does Olostep have a free plan?

How fast can Olostep process large batches of URLs?

What can I actually build with Olostep?

Do Olostep credits expire?

Can Olostep bypass bot detection like Cloudflare?

How much does Olostep cost compared to other web scraping APIs?

Estimated website traffic data for Olostep

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7.4K

Monthly Visits

~8.0K avg/3mo

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