ModelSaid

Proof

We pointed the product at ourselves

Anyone can claim their software works. The useful version is to run it on your own company, publish the score, and show what happened on the day it dropped. So that is what this page is.

ModelSaid AI readiness

100/100

Strong

Scored by the same free checker you can point at your own site. The categories below use its real weights, so your result is directly comparable.

AI readiness score by category
Discovery filesllms.txt, llms-full.txt, ai.txt25/25
Crawler access10 of 10 AI crawlers allowed30/30
Structured dataOrganization, WebSite, BlogPosting25/25
Content readinessTitle, description, sitemap, h120/20

Last 30 days

94 to 100

  1. 01

    Score dropped

    A deploy changed a header and two AI crawlers lost access. The daily check caught it the same morning.

  2. 02

    Cause identified

    The diff pointed at the exact rule that changed, and which crawlers it affected. No searching.

  3. 03

    Fix opened as a PR

    Auto Fix wrote the change against our repository and opened a pull request. Nothing was pushed to the main branch.

  4. 04

    Back to full marks

    A human reviewed and merged it. The next check confirmed the recovery.

Days monitored
30

Continuously, without anyone remembering to check.

Checks run
120

Across discovery, crawlers, structured data and content.

Manual audits
0

The point is that nobody has to do this by hand.

What it actually took

Four steps, in this order. Doing them out of order is the usual reason an AI visibility project stalls: there is no point automating a measurement you have not fixed the basics for.

  1. 01

    Measure before changing anything

    Run the free check and write the number down. Without a baseline you cannot tell a real improvement from a model that happened to answer differently that day.

  2. 02

    Fix the things machines read

    Discovery files, crawler access, structured data, titles and descriptions. Unglamorous, quick, and the reason most businesses are invisible to AI assistants.

  3. 03

    Let the fixes be written for you

    Connect the repository and Auto Fix proposes the change as a pull request. You review and merge. It never pushes to your main branch.

  4. 04

    Keep watching, because answers move

    Models update, competitors change, and a deploy can undo months of work in one header. Continuous checks turn that from a discovery months later into an email the same morning.

Your company runs the same thing

Nothing above is a bespoke setup we built for ourselves. It is the product, on the same plans anyone can subscribe to.

Discovery files, generated
llms.txt, ai.txt and robots.txt built for your site by the free tools, so AI crawlers are told what to read instead of guessing.
Crawler access, verified
We check whether each major AI crawler can actually reach your pages, and tell you which rule is blocking the ones that cannot.
Structured data that models trust
Organization and business schema so your name, address and services are facts a model can read, not prose it has to interpret.
Answers to what buyers ask
Content drafted around real buyer questions, scored before you publish, so the page is worth citing when someone asks.

See where your business stands today

The check is free and takes about a minute. You get the same scorecard shown above, for your own site, with the specific things to fix listed in order.