Full Visibility Machine
Automated SEO/GEO operations that prove themselves
The problem
Visibility work is normally invisible and unverifiable: a person runs checks, applies fixes, and nobody can tell afterwards what was actually done — or whether the fix survived the next deploy.
The solution
The machine runs every day: it pulls Search Console and GA4 data per site, checks indexation, canonical tags, structured data, sitemaps, speed and on-page content, then turns findings into tasks. Patches are prepared and applied through a git-based deploy chain that always backs up first.
The part that makes it different is verification: every published page is checked on the live site through a four-step chain — HTTP 200, correct canonical, JSON-LD, and a link to the machine description (llms.txt). The result is machine-generated and public. If verification fails after a deploy, the system reverts the change by itself.
It also learns in a disciplined way: when a mistake happens, the cause, a rule and a pre-publish check are written down, and a lesson is stored only when evidence is attached.
Verifiable proof
Each item is checkable — a command, a public URL, or a number measured on the live system.
- 197 operational modules · 53 dedicated guard suites
- 55/55 guard tests green (node dodaci/testovi.mjs)
- 11/11 live pages pass: HTTP 200 → canonical → JSON-LD → llms.txt
- 1,656 generated report files · 21 scheduled tasks running
- OKO ("the eye"): takes a real screenshot of each site and reads it with a local vision model (qwen2.5vl) — 16/16 tests, including "an unknown domain invents no findings"
- Automatic rollback when post-deploy verification fails
- Daily report delivered; failures are reported instead of hidden