Olostep

Olostep is a web data infrastructure platform built by Olostep Technologies, Inc., designed to power AI agents and applications that need to search, scrape, crawl, and structure data from the live web. The company describes its mission as building "the infrastructure AI agents need to do real work on the web," positioning the product as the data layer for what it calls "the web's second user" — AI agents operating at machine scale. The platform is actively used in production and offers a free trial tier with no credit card required.

What It Is

Olostep is a unified web data API that consolidates seven core capabilities — scraping, crawling, site mapping, batch processing, web search, AI-powered answers, and scheduled monitoring — into a single REST API with native Python and Node.js SDKs. It handles the infrastructure complexity of headless browsers, residential proxies, and CAPTCHA solving so developers don't have to maintain those systems themselves. The platform is designed for AI startups, developers, AI engineers, data scientists, and research teams that need reliable, structured web data to power products, enrich datasets, and automate workflows.

Core API Endpoints

Olostep's API surface is organized around seven endpoints, each targeting a distinct data acquisition job:

• /scrapes — Converts any URL into LLM-ready Markdown, HTML, screenshots, PDFs, or structured JSON, including JS-rendered pages.
• /crawls — Crawls websites at scale, collecting content from subpages with configurable depth and URL pattern controls; supports webhook notifications on completion.
• /maps — Discovers every URL on a website using sitemaps and on-page links, with path-pattern filtering and pagination.
• /batches — Processes up to 10,000 concurrent URLs in a single batch in 5–8 minutes; multiple batches can run in parallel for millions of concurrent requests.
• /searches — Accepts natural-language queries and returns ranked, relevant web links with titles and descriptions.
• /answers — Searches the live web, reads pages, cross-validates across sources, and returns AI-generated answers in a user-defined JSON schema; returns NOT_FOUND when facts cannot be verified rather than hallucinating.
• /monitors — Creates scheduled web monitors from natural-language instructions, tracking changes on pages or across the web and delivering alerts via email, webhook, or SMS.

Developer Experience and Integrations

The platform provides object-oriented SDK clients for Python (pip install olostep) and Node.js (npm i olostep), plus a CLI (npx -y olostep-cli@latest) for terminal-based scraping, crawling, and batch processing. An MCP (Model Context Protocol) server (npx -y olostep-mcp) enables integration with any MCP-compatible AI client, including Cursor, Claude, Windsurf, VS Code, Cline, JetBrains, Gemini CLI, OpenAI Codex, Amazon Q, Copilot, Warp, Zed, and others. Official integrations also include n8n, LangChain, Zapier, Relay, Mastra, Apify, Smithery, LM Studio, Perplexity, Qodo Gen, Roo Code, and Deno, among others. Payments are processed through Stripe.

Target Use Cases

Olostep's use case pages highlight five primary application areas:

• AI platform powering — Real-time web data for agents, workflows, and RAG pipelines.
• Sales lead enrichment — Transforming prospect websites into structured company intelligence, contact information, and enrichment signals at scale.
• Deep research and competitive intelligence — Multi-source information retrieval for market analysis, pricing monitoring, and product update tracking.
• SEO and AI search visibility — Extracting every URL on a website, analyzing site architecture, and measuring visibility across search engines and AI answer platforms.
• Brand protection — Monitoring marketplaces, extracting listing data, and automating counterfeit detection workflows.

Architecture and Scale Claims

According to the Olostep about page, the platform claims access to 50 billion+ pages, handles an average of 1 billion+ API calls, and maintains 99.9% API uptime. The company states it supports up to billions of requests per month for enterprise customers. The batch endpoint is described as a "unique feature on the market purpose-built for large-scale concurrent processing," with a demonstrated throughput of approximately 48,752 URLs per minute across parallel batches. All requests use JS rendering and residential IP addresses by default; failed requests are not billed.

Team and Background

Olostep Technologies, Inc. was co-founded by Hamza (CEO, previously co-founded Zecento, an Italian AI e-commerce tool) and Arslan (previously engineered at Sameday, a YC W23 company, and other YC startups including Legora and Zenfetch; CS student at Stanford). The team also includes senior software engineers, an AI/ML engineer, a product engineer, and a design engineer. The company is incorporated in the United States and describes itself as "Made in Italy | United States." It is backed by Vento Ventures and Perplexity (listed as investors on the about page).