Analytics and monitoring decision

SISTRIX

A narrow replacement (keyword rank checks, a simple visibility score, history and basic crawler) is realistic for a competent engineer in about a week, but you cannot reproduce SISTRIX's proprietary dataset, historical depth, or scale without significant time and data costs—so keep paying if you need full-scale coverage.

Visit website
You pay

$119/mo

$1,428/yr

Read off the official pricing page.

You’d pay instead

$50one-off30 h to build

$100/mo8 h/mo upkeep

On cash alone, building overtakes the subscription at 1 seat.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • Collect SERP positions for a set of keywords, compute a simple visibility score, store historical positions, surface domain/keyword reports and run an on-page crawler for a project.

What it still won’t have

  • Proprietary dataset (visibility index across 100M+ domains and long historical depth)
  • Scale (fast queries across huge keyword/domain sets)
  • Built-in credit/usage model and integrations provided by SISTRIX

What remains hard

  • Proprietary dataYou’ll get access to the Visibility Index of over 100 Million Domains in 30+ countries.
  • Proprietary dataData from over 100 million domains is analysed and presented in fractions of a second.
  • Infrastructure at scaleSISTRIX MCP Servers: Now available for all SISTRIX users
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 1 seat.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal SEO visibility tracker using Node.js + Express, Postgres, and a headless-browser or SERP API. Implement: (1) keyword scheduler that queries SERPs and stores top-100 positions; (2) visibility-index computation (weighted sum of ranks); (3) domain and keyword history endpoints (JSON + CSV export); (4) a small React UI to view domain overview, keyword trends and run an on-page crawl for a project (JS-rendered page checks). Out of scope: recreating SISTRIX's 100M-domain dataset, enterprise multi-tenant role/audit features, and advanced content-marketing tooling. Include error handling, retry/backoff for API calls, credit usage logging, and unit tests for core functions.
How we checked3 sources · 2/3 runs agreed · evidence score 52

How the score was reached

  • Partly verdict base52
  • 3 cited sources+3
  • Price verified on pricing page+3
  • Hard moats found in the evidence-6
  • Evidence score52

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 3

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 3 moats quoted from the page