What is AI content optimization?

AI content optimization is rewriting an existing page so an assistant can lift a claim out of it and attribute that claim to you. It is measured differently from SEO: not a ranking position, but a citation rate — the share of successful runs in which a model attached a link to your own domain. Attensira has no page score and no readability grade; the number that moves is the citation rate on the prompts the page is meant to answer.

How do you make content more AI-readable?

The agent reads the stored answer text for the prompts a page targets, along with the pages that were cited instead, then rewrites the sections that failed to give an assistant a self-contained, attributable claim. The rewrite is committed to a fresh branch and opened as a pull request against the repository the page lives in, with the body naming the page, the finding, and why the edit answers it.

How do you decide which new pages to suggest?

From the prompts where no page of yours was cited at all. Attensira buckets every cited domain by kind — your own, a competitor, an AI platform, a reference site, or a third party — and the third-party bucket is the narrowest and the only one where a citation is genuinely winnable. A gap there, on a prompt you track, is what turns into a proposed page.

What's the competitor research process?

You add a competitor by domain and Attensira scores them over the answers it has already collected — the same mention and citation rates, on the same denominator as yours, with no extra runs and no prompt slots consumed. Because the rates are independent, they can sum past 100%: one answer can name four brands. From there the agent reads the pages that were cited and what made them quotable.

Can I review suggestions before implementing them?

Every change is a pull request you review, one action at a time. The agent never merges, never pushes to your default branch, never pushes twice to the same branch, and never touches CI configuration or workflow files. Draft mode makes every pull request a GitHub draft. Note that Attensira cannot read your branch protection settings — if your repository auto-merges on green, its pull requests will merge too unless draft mode is on.

Can Attensira tell me what a citation was worth?

No. Attensira cannot tell you that a mention produced a visit, that a citation produced a signup, or that either produced revenue — there is no identity join between an assistant's answer and a later visitor. What it can show is the citation rate on the prompts a page targets, before and after the edit, with the number of runs behind each figure and a significance test between them.

Content Optimisation

Make Your Pages Worth Citing

Your pages were written for humans. AI reads them differently — it extracts entities, facts, and relationships. If your content isn't structured for that, AI simply ignores it. Attensira starts from the answers that named a competitor and not you, rewrites the page that should have been cited, and opens a pull request against your repository. You merge it.

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Analyse Your Content

We scan your pages and identify what AI struggles to understand and cite.

Rewrite for AI

Get AI-optimised versions of your content that models can parse, extract, and cite.

Target prompts

Optimise for the exact buyer questions you already track, per model and per country.

Suggest New Pages

We research gaps and recommend content you should create to fill them.

app.attensira.com

Content Studio

Analysing

pipedrive.com/features

Cited: 8% · n=25→PR open

Issues Found

🔴Entity definition

🔴Value propositions

🟡Pricing data

🟡Comparison context

Suggested Rewrites

"Pipedrive helps you manage your sales"

"Pipedrive is a CRM platform that tracks sales pipelines, automates follow-ups, and provides forecasting for teams of 1-500 users"

Claim now self-contained

Approved

"Our integrations work seamlessly"

"Pipedrive integrates with 400+ tools including Slack, Zoom, Google Workspace, and Zapier"

Qualifier in the same sentence

Decline

"Pricing that scales with you"

"Pipedrive pricing starts at $14/user/month (Essential) up to $99/user/month (Enterprise), billed annually"

Source named inline

Decline

+2 more suggestions available

Page-level

Analysis of every URL on your site

95%

Significance bar before a change is reported

Readable model surfaces; a new workspace starts on two

Per-prompt

Rewrites targeted to specific prompts

Everything you need to optimise for AI

From reading the pages behind a finding to the pull request that carries the edit.

Vague entity references🔴

Missing structured data🔴

No comparison framework🟡

Outdated statistics🟢

Content Analysis

We scan every page and identify exactly what AI struggles to understand — vague entities, missing facts, and weak structure.

Original:

"We help companies grow"

AI-Optimised:

"Attensira measures how often assistants name your brand, reported as a mention rate with its run count, per model surface"

AI-Readable Rewrites

Get specific, citeable rewrites that replace vague marketing copy with entity-rich claims AI models can extract.

Optimising for (runs in window):

best CRM for small businessn=21

CRM vs spreadsheetn=21

affordable CRM softwaren=14

Prompt Targeting

Specify the prompts you want to appear in — we optimise your content to match how AI answers those questions.

Countries tracked:

United States

United Kingdom

Germany

France

Country coverage

A prompt runs per country, at most once per model per day, and its rates are reported per country rather than averaged into one number.

Your content coverage for "best CRM software":

pipedrive.com✓ Mentioned

Pricing comparisonmissing

Integration ecosystemweak

Use case examplesmissing

Content Gap Analysis

Find what topics you're missing to get mentioned for target prompts. See exactly where competitors have content and you don't.

How the edit reaches you:

Branch openedattensira/pricing-faq

Pull requestawaiting your review

Mergeyours, never ours

It ships as a pull request

The edit lands on a branch in your own repository through the first-party GitHub App. Attensira never merges it and never pushes to your default branch.

How it works

Connect your site, review the proposed edits, merge the ones you want — then read the rates over whole days.

Connect Your Site

Add your domain and we start processing your pages automatically in the background.

Search Your Pages

Find any page on your site and read the prompts, answers and citations it is implicated in. Nothing here scores the page.

Review Results

Get specific rewrites tailored to the prompts you track.

Accept or Decline

Review each suggestion. Accept what works, decline what doesn't. You're in control.

Merge & Track

Merge the pull request, then compare whole days: a delta is only reported once it clears a two-proportion z-test at 95%.

Why This Matters

AI doesn't read like humans

When ChatGPT or Claude answers a question, they don't scan your page like a person would. They extract entities, relationships, and facts. If your content is written with fluffy marketing copy, AI simply can't cite it — even if the information is technically there.

Attensira has published no study of which page shapes get cited, and this page will not pretend otherwise. What it does show you is your own evidence: the stored answer text for every run, which pages were cited alongside it, and the rate with its run count. The proposed edits are argued from that, not from a rule of thumb.

Entity Clarity

Define who and what you are explicitly — not with vague claims, but with verifiable facts.

Structured Facts

Present information in formats AI can extract: tables, lists, and clearly labelled data points.

Comparison Context

Show how you relate to alternatives so AI knows when to recommend you over competitors.

Schema Markup

Give AI a structured data layer it can read directly — product details, FAQs, and relationships between entities.

Citation rate on the prompts this page targets

Illustration of the metric shape. Not a measured result, and not a typical one — Attensira publishes no outcome figures.

Before8% · n=25

After28% · n=25

Change+20 pts

Two-proportion z-testclears 95%

Pull requestmerged by you

FAQ

Frequently Asked Questions

Have more questions?

Book a demo and we'll answer them personally.

Book a Demo

AI content optimization is the process of restructuring your existing web pages so that AI models like ChatGPT, Claude, and Google AI can understand, extract, and cite your content. Unlike traditional SEO, which focuses on keyword placement and backlinks, AI optimization focuses on entity clarity, structured facts, comparison context, and schema markup — the signals AI models use to decide what to include in their answers.

AI models parse content differently than humans. We analyse your existing pages for clarity, structure, and entity recognition. Then we rewrite sections to be more explicit, add structured data, improve heading hierarchy, and ensure key information is presented in ways AI can easily extract and cite.

Any question you can put to an assistant, from 'best CRM software' to 'CRM for small real estate teams'. A prompt is tracked per model and per country, and grouping related prompts into a topic pools their runs, so a topic clears the significance test sooner than any single prompt inside it.

We analyse the prompts you want to rank for, identify content gaps where you're not being cited, and research what your competitors have published. We then recommend new pages that would fill those gaps, complete with outlines and target prompts.

For each topic you want to rank for, we identify which competitors are currently being cited by AI models. We analyse their content structure, topics covered, and what makes them citeable. Then we provide recommendations for how to create content that surpasses theirs.

Absolutely. Every suggested change — whether it's a rewrite, a new section, or a new page — is presented for your approval. You can accept, modify, or reject each recommendation. Nothing changes on your site without your explicit approval.

A traditional tool ends at a recommendation and a score. Attensira has no page score and no readability grade: it ends at a pull request in your repository, and the evidence behind it is the verbatim answer text an assistant produced, kept so the finding can be re-checked. The number that moves is the citation rate on the prompts the page targets.

Attensira cannot tell you that a mention produced a visit, that a citation produced a signup, or that either produced revenue — there is no identity join between an assistant’s answer and a later visitor, and there is no timeline we can honestly promise. What it can show is the citation rate on the prompts a page targets, before and after the edit, with the number of runs behind each figure and a two-proportion z-test at 95% between them.

Optimisation is just the start

Once the edit is merged, the rest of Attensira is what tells you whether anything moved: the prompts, the answers behind them, and the rates with their run counts.

Prompt Tracking

Put your buyers’ questions to each tracked model on a schedule, keep the answer text, and read the mention and citation rate with the run count behind each.

The agent

It reads your tracked prompts, models, answers and citations, works out what changed, and acts on it — scoped to one workspace and stopped for an explicit yes before anything irreversible.

GitHub

A first-party GitHub App, scoped to the repositories you select. Every fix arrives as a pull request, and Attensira never merges it.

What it does not do

It does not publish. The edit arrives as a pull request against the repository the page lives in; Attensira never merges it, never pushes to your default branch, and never pushes twice to the same branch.
It does not score a page. There is no visibility score and no sentiment metric in Attensira — the inputs are Mention rate, Citation rate and the answers behind them, each with its sample size attached.
It cannot prove the edit caused the movement. A delta is only reported once it clears a two-proportion z-test at 95% significance, and nothing joins an answer a model gave someone to a person who later arrived at your site.
It cannot see faster than collection. Each Prompt × Model × country runs at most once per workspace-local calendar day, so the effect of a merged pull request shows up over whole days, not hours.

The full account is at docs.attensira.com/reference/limitations.

Which plans include it

Included on every plan: Starter, Growth and Business.

What varies by plan is how much evidence sits behind a finding — sampling depth, how many Prompts you track, and whether the agent writes against a stored brand profile. Those numbers live on pricing, and how an edit reaches you is documented at docs.attensira.com/agent/github.

By Karl-Gustav KallasmaaLast updated 4 September 2026

Your content ranks on Google. Does AI cite it?

Find out which pages AI can't parse, get targeted rewrites for the prompts you care about, and close the content gaps your competitors have already filled.

Get Started Book A Demo

Cancel anytime

Make Your Pages Worth Citing

Analyse Your Content

Rewrite for AI

Target prompts

Suggest New Pages

Everything you need to optimise for AI

Content Analysis

AI-Readable Rewrites

Prompt Targeting

Country coverage

Content Gap Analysis

It ships as a pull request

How it works

Connect Your Site

Search Your Pages

Review Results

Accept or Decline

Merge & Track

AI doesn't read like humans

Entity Clarity

Structured Facts

Comparison Context

Schema Markup

Frequently Asked Questions

What is AI content optimization?

How do you make content more AI-readable?

What prompts can I optimise for?

How do you decide which new pages to suggest?

What's the competitor research process?

Can I review suggestions before implementing them?

How is this different from traditional content optimization?

Can Attensira tell me what a citation was worth?

Optimisation is just the start

Prompt Tracking

The agent

GitHub

What it does not do

Which plans include it

Your content ranks on Google. Does AI cite it?

Everything you need to optimise for AI

Content Analysis

AI-Readable Rewrites

Prompt Targeting

Country coverage

Content Gap Analysis

It ships as a pull request

How it works

Connect Your Site

Search Your Pages

Review Results

Accept or Decline

Merge & Track

AI doesn't read like humans

Entity Clarity

Structured Facts

Comparison Context

Schema Markup

Frequently Asked Questions

What is AI content optimization?

How do you make content more AI-readable?

What prompts can I optimise for?

How do you decide which new pages to suggest?

What's the competitor research process?

Can I review suggestions before implementing them?

How is this different from traditional content optimization?

Can Attensira tell me what a citation was worth?

Optimisation is just the start

Prompt Tracking

The agent

GitHub

What it does not do

Which plans include it

Your content ranks on Google. Does AI cite it?