ContentGrapher maps your content's concept structure, diagnoses what AI can retrieve and what's structurally missing, and tells you exactly what to write next.
How an LLM traverses your page: dashed nodes are concepts a retrieval pass would expect but didn't find.
Free to start. Pay when it’s useful. 5 free analyses, then from $29 for a first client review. No subscription. Analyses valid 12 months.
Your content has blind spots.
AI can't retrieve what it can't connect.
ContentGrapher maps the gaps.
“When someone asks ChatGPT a question in your domain, the model isn't running a keyword search; it's reading content. If your concept structure is weak, you don't just rank lower; you may not appear at all.”
Sentence-level instructions: what to add, what to clarify, which relationships to make explicit. Not a grade. Not a keyword list. A brief your writers can act on today.
ContentGrapher doesn't just find gaps. It tells you which topics are core to your page's retrieval role, which are supportive context, and which are pulling you off-scope. Stop writing everything; write what matters.
Map the concept graph your content actually contains: what's well-integrated, what's weakly connected, what's missing entirely.
Discover which concepts your content implies but never states, and which relationships an AI would need to retrieve and cite you accurately.
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↓ content fetched from any public URL, no account neededYour concept graph appears
↓ integration state per concept, 8 diagnostic dimensionsGet your writing brief
↓ exact sentences to add, page architecture, delta view. Sign in to save your history.In our model, every page has one dominant job in the retrieval ecosystem. ContentGrapher identifies it.
Mixed-role pages compete with themselves. A page that both explains and guides rarely earns either citation cleanly.
Is this page scoped correctly? No other tool answers this. The Boundary Layer tells you which concepts to deepen here, and which to move to their own page before they dilute the signal you're trying to build.
Structured, typed, actionable. Not a score. A writing brief.
ContentGrapher maps your page's concept structure: solid nodes are what you cover, dashed nodes are what's missing.
Coverage isn't completeness. Matching your competitors' keyword list doesn't tell you whether your explanation makes sense on its own.
Knowing you're not being cited doesn't tell you why. ContentGrapher answers the prior question.
We don't write content. We tell you what's missing from what you've already written.
ContentGrapher is for content teams who already care about quality and want to make sure that quality is legible to the systems now doing the finding.
Analyze. Write. Re-analyze. See exactly what moved.
Start free. 5 analyses, no card required. When you're ready, packs start at $29.
Starts with your 5 free analyses
If you charge for content strategy, a single recommendation backed by a ContentGrapher analysis is worth more than the pack costs.
Run a Full AuditStarts with your 5 free analyses
Starts with your 5 free analyses
Analyses valid for 12 months from purchase.
No subscription. No monthly commitment. Built for people who bill by the deliverable, not by the month.
All analyses stored in your history. Re-analyze any page, any time.
Every other tool in this category is built on correlation: matching what's ranking. ContentGrapher is built on first principles: mapping what your topic and audience actually require.
AI retrieval systems (RAG-based tools like Perplexity and ChatGPT's web search) don't read your page the way Google does. They don't keyword-match. They retrieve passages that contain structurally complete explanations of what someone asked.
Coverage-based tools (Clearscope, Surfer, MarketMuse, Semrush's content audit) are built on correlation. They identify what top-ranking pages have in common and tell you to match those patterns. That's a legitimate input for traditional search. But correlation tells you what's popular, not what's correct.
ContentGrapher asks a different question: given your topic and your audience, what concepts must be explained, at what depth, and in what relationship to each other? If your content doesn't answer that completely, AI skips it.
Those tools are externally anchored: they benchmark your content against what's currently ranking. If top results cover keyword A and entity B, they tell you to add them. That's useful for traditional search, but it doesn't tell you whether your explanation is coherent on its own terms.
ContentGrapher is internally anchored. It builds the ideal explanation framework for your specific topic and audience from first principles, not from what competitors have published. If every top-ranking page on a topic is missing a key concept, coverage tools won't tell you. ContentGrapher will.
It also diagnoses something the others don't: whether your page is trying to do too many jobs. Mixed-intent pages dilute retrieval signals. ContentGrapher tells you what scope this page should own, and what belongs elsewhere.
Monitoring tools tell you where you're appearing, or not. That's useful data. But knowing you're invisible doesn't tell you why.
ContentGrapher answers the prior question. Before you can fix the problem, you need a diagnosis: which concepts are underexplained, which relationships are implied but never stated, which parts of your page are doing the right job and which are creating noise. That's what the analysis delivers.
Not in the way people assume. The skyscraper technique was a correlation play: longer content correlated with authority signals in traditional search, so the strategy was to go longer. That correlation was real, but it was describing a proxy, not a mechanism.
In AI retrieval, what matters is structural completeness per passage. RAG systems chunk your content into segments and retrieve the most relevant chunk, not the whole page. A 6,000-word page with one structurally complete passage performs better than a 500-word page with none. But a 500-word page with three well-integrated concepts outperforms a 3,000-word page where every concept is weakly connected.
For training data, it's similar: consistent entity naming and clear concept relationships encode more accurately into model weights than raw volume. Token count is not quality. Information density per token is.
That second part is the gap correlation-based content strategy was never designed to close.
This is the question the skyscraper era left unanswered. The answer depends on your page's primary retrieval role.
ContentGrapher classifies every page by the job it's doing: explaining what something is, guiding someone through a task, comparing options, evaluating fit, or converting. Each of those jobs has a natural scope. When a page tries to do more than one, it creates a diluted retrieval signal; AI can't cleanly classify what it's for, so it retrieves it for fewer queries.
For every concept in your content, ContentGrapher tells you whether it's core to this page's role, supportive (worth a brief mention), belongs elsewhere (needs its own page), or excluded (actively weakening the signal). That's the answer to where you stop: when you've fully covered what's core and handed off what belongs elsewhere via a clear link pathway.
ContentGrapher is an analysis tool. Its output is a writing brief: specific additions, clarifications, and sentence-level guidance, not generated prose.
The reason is structural: AI writing tools generate from patterns. ContentGrapher diagnoses against a first-principles framework built for your topic and audience. Those are different jobs. Analysis tells you what needs to exist and why. Writing can follow from that, whether you write it, a writer does, or an AI does with the brief as input.
Analysis-first isn't a current limitation. It's the design principle.
It means your content contains the concepts and relationships an AI needs to retrieve and cite it accurately, for your specific topic and your specific audience.
ContentGrapher produces two outputs per analysis. First: a map of what's actually in your content, covering every concept, its integration state (well-integrated, weakly integrated, underexplained, or naming-inconsistent), and the explicit and implied relationships between them. Second: an explanation framework built from the topic itself, specifying what a structurally complete treatment of this subject requires, derived from first principles, not from what's currently ranking.
The gap between those two is your writing agenda.
Two types of people use it.
Content strategists, SEO leads, and editors who audit content libraries and need to show stakeholders why traffic and pipeline are decoupling, and what specifically to fix. ContentGrapher gives them an observable, exportable diagnostic: which pages are underexplaining, by how much, and what the fix looks like.
Content writers and technical writers who want a feedback loop. You write, you analyze, you get specific writing guidance, you edit, you re-analyze, and you see exactly what changed. Not a grade. A diff.
If you charge for content strategy, the deliverable ContentGrapher produces is the kind of thing clients pay for. One structural audit backed by this analysis is worth more than the pack costs.
Paste a URL or your content into the analyzer. The first 5 analyses are free, no card required. You'll see your concept graph, integration states, and a writing brief within a few minutes.
When you're ready to go deeper, packs start at $29 for 10 analyses. No subscription. Analyses valid for 12 months.
Every URL you analyze is saved to your dashboard: concept graph, structural gaps, writing brief. Re-run after edits and see exactly what closed. Paste a URL to start, no account needed. You have 5 free full analyses to see whether this changes how you work.
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