Assistants describe Nortium without pricing or plans; competitors expose structured pricing the model can cite.
nortium.com/pricing · no structured data
Growth engineers
AI visibility that behaves like code, not a dashboard.
CitePatch treats each fix as a reviewable diff and each deploy as a change the Monitor keeps watching. Patches open where your content already lives — a pull request, a CMS draft — and every result is traceable end to end.
Observed
Assistants describe Nortium without pricing or plans; competitors expose structured pricing the model can cite.
InferredConfidence: 4/5
The evidence suggests missing structured data, not missing content.
Proposed
Add Product/Offer JSON-LD to the pricing route.
Effort: SRisk: low
app/pricing/structured-data.tsx
"@type": "Product","name": "Nortium""name": "Nortium", "offers": {"@type":"Offer","price":"49"}The difference
What changes when you run the loop
Without CitePatch
- AI-visibility work lives outside your stack, in dashboards you can't diff.
- Suggestions are copy-paste, with no review or rollback.
- No re-observed record, so real wins and noise look identical.
- Nothing is versioned — you can't audit what changed or why.
With CitePatch
- Fixes open as pull requests in the repo that owns the page.
- Every change is reviewed, merged and revertible like any code.
- The Monitor's re-observed record makes each result traceable.
- Prompt → answer → citation → page, auditable end to end.
The loop, as a pipeline
Observe, patch, and measure — without leaving your stack.
No copy-paste suggestions and no black box: the same discipline you'd expect from a well-run test.
- 01DiscoverFind the buying questions worth tracking.
- 02ObserveSee how AI answers them, verbatim.
- 03DiagnoseTrace each gap to the evidence behind it.
- 04PatchDraft the fix — an edit or a whole new page — grounded in your facts.
- 05ApproveA human reviews and signs off.
- 06DeployShip it where your content lives.
- 07VerifyRe-observe the result on the Monitor's normal cadence.
- 08LearnKeep what worked; queue the next gap.
- ↩ the loop is deliberate
Division of labour
You own the repo. CitePatch proposes the diff.
What stays yours
- The repository, review process, and deploy pipeline
- Merging, reverting, and the final say on every change
- Where CitePatch can and can't open changes
What CitePatch runs
- Grounding every patch in your approved facts — nothing invented
- Opening the edit or the new page as a pull request or CMS draft
- Keeping the Monitor's before/after record for every shipped change
- Exports and an API so it fits your existing workflow
What's in the record
Auditable from prompt to deploy.
Every artefact carries its epistemic state, so a result never claims more than the data supports.
- Observed
Raw per-surface answers and citations, captured verbatim.
- Inferred
The prompt-to-page chain behind each gap.
- Proposed
A grounded diff, ready to review in your own tools.
- Verified
The Monitor's dated before/after for the same questions.
One fact, all the way to a patch
"@type": "Product","name": "Nortium""name": "Nortium", "offers": {"@type":"Offer","price":"49"}Another role on your team?
For technical teams
Frequently asked questions
How do patches reach my codebase?
As a pull request in the repo that owns the page, or a draft in your CMS. You review the diff, then merge and deploy on your own terms.
Can the model invent facts in a patch?
No. Every patch is grounded in your approved Brand Truth. If a fact isn't approved, it can't ship in a change.
Is there an API and exports?
Yes. Observations, evidence, and the Monitor's re-observed results are available via exports and an API so you can wire them into your existing reporting.
Put AI visibility under version control.
Start with a Free Audit, or book a demo to see a patch open as a pull request on your own content.