TEARDOWN 48 · REVIEWED 2026-08-19
JetOctopus
JetOctopus is a cloud-based technical SEO platform that crawls the site you point it at, reads your own server log files to see how search and AI bots actually behave, and layers in Google Search Console and Analytics data — the same category as Oncrawl, Lumar, and Botify. Unlike those three, it publishes a self-serve, usage-based price instead of requiring a custom quote.
Crawling a single site is a known weekend build; matching JetOctopus's pipeline that classifies 40+ bot types out of raw log files and joins that against crawl, Search Console, and Analytics data in one dashboard is a genuine data-engineering project most teams won't build for one site.
What you lose building it yourself
- ✕Classifying 40+ bot types (Googlebot, Bingbot, GPTBot, ClaudeBot, and others) from raw log lines
- ✕Joining crawl, log, Search Console, and Analytics data into one dashboard
- ✕Cloud crawl throughput up to 250 pages/second without your own machine or script choking
- ✕Backlink data joined against crawl and log data out of the box
Why people still pay
The join itself is a weekend script against one small log file; keeping bot classification accurate as user-agents change, processing production-scale logs without running out of memory, and having Search Console and Analytics data already joined into one dashboard is the ongoing engineering work most teams would rather rent than own.
BUILD YOUR OWN · WEEKEND CRAWL, HARDER LOG PIPELINE
A basic site crawler is a realistic weekend build for an AI coding tool, same as any other technical SEO crawler. Reliably classifying 40+ bot types from raw server logs and joining that against crawl, Search Console, and Analytics data — without silently dropping rows at real log volumes — is a genuine data-engineering project, closer to a multi-week build than a weekend one.
StackPlaywright or Puppeteer for the site crawl · a log parser (a Python script matching user-agents against a maintained bot list) · SQLite to join crawl, log, and Search Console export data by URL.
Build two Python scripts. First, a crawler using Playwright that follows same-domain internal links up to 500 pages, recording URL, status code, and title to a SQLite table. Second, a log parser that reads a standard Apache/Nginx access log file, extracts each request's URL, user-agent, and timestamp, and matches user-agents against a hardcoded list of 10 known bots (Googlebot, Bingbot, GPTBot, ClaudeBot, and 6 others), writing matches to a second SQLite table and discarding anything that doesn't match. Join the two tables on URL and output a CSV showing, per page: whether it was crawled, which of the 10 bots hit it, and how many times each. Cap the log file read at 1GB for this pass.
Similar tools
Free alternative: LibreCrawl — covers the free crawl side of the job with no URL cap; pairing it with GoAccess (a free, actively-maintained open-source log analyzer) covers basic log parsing, but neither classifies bot traffic by type or joins crawl, log, Search Console, and Analytics data into one dashboard the way JetOctopus does.
Vendor's own claim
"100% full data, no blind spots"
https://jetoctopus.com/ · RETRIEVED 2026-08-19
QUESTIONS
How is JetOctopus's pricing different from Oncrawl, Lumar, or Botify?
Those three quote custom enterprise pricing only. JetOctopus publishes a self-serve base plan — €383/month billed annually for 1M crawl pages and 1M log lines, with extra volume sold à la carte — and offers a 7-day free trial with no credit card required.
Does JetOctopus maintain its own web-wide index like a backlink tool?
No — it only crawls the site(s) you point it at and analyzes your own uploaded server logs. There's no persistent, web-scale index behind it, the same pattern as Oncrawl and Lumar.
What does classifying '40+ bot types' actually mean?
JetOctopus reads your raw server log files and matches each request's user-agent against a maintained list of more than 40 known crawlers — including Googlebot, Bingbot, and AI crawlers like GPTBot and ClaudeBot — so you can see which bots actually visited which pages, not just which pages a simulated crawl found.