Content Engine
Content AI can't get anywhere else. Every claim, sourced.
We research your market across the live web, weave in your own proprietary data, and write block-by-block where every fact links to where it came from - then auto-score it citation-ready before you ever see it.
It researches across 7 live platforms
How it works
Great content isn't written - it's researched, sourced, and graded
Gathers real intelligence
21 targeted queries across 7 platforms per topic - real Reddit threads, YouTube transcripts, news, podcasts and long-form writing. Not a rewritten search result.
21 queries · 7 platforms · ~10 sources per article
Builds a sourced fact library
Every finding becomes a cited evidence card: a claim, a quotable line, and a live source URL. Your own proprietary data and first-party knowledge feed the same library.
5 feeds incl. your proprietary data
Writes block-by-block, cited
Each section must declare which evidence it used before it is written. If a claim has no source URL behind it, the claim doesn't get made.
No URL, no claim - the server enforces it
Graded before it publishes
Every draft is scored on 5 pillars across 17 checks before it publishes. Our bar is 70+, and you can see each article's AEO Rank in Studio.
AEO Rank 5 pillars / 17 checks · 70+ bar
Inside the Content Engine
Every fact logged to its source
Before a single sentence is written, the research is ranked into evidence cards and each card is assigned to a specific block. This is the ledger behind one article.
"Families ask about overnight coverage first - not price. We rebuilt our intake script around it."
"The 3am fall is the moment adult children start searching." - transcript 4:12
New 2026 CMS rule ties home-health reimbursement to documented care-plan reviews.
The "remove the brand name" test
"Virtual assistants reduce costs by up to 70%."
Could be anyone's. Strip the brand name and it fits every competitor's page word for word - so AI has no reason to name you.
"Across 1,200 support conversations we handled last quarter, live chat resolved 71% with no human handoff - median first reply 19 seconds."
Your unfair advantage: a number with a sample size that AI can't find anywhere else - so it quotes it and names you.
"If you remove the brand name, could this paragraph appear on a competitor's website? If yes, it's not original data."
Format example only - illustrates the shape of an original stat, not a real client result.
Why it works
AI has a trust hierarchy - and original data sits at the top
Proprietary data and first-hand expertise sit at the top; rewritten Wikipedia sits at the bottom. Give AI a number it can't find anywhere else, and it cites you by name.
Where does the research for each article come from?
The engine runs 21 targeted queries across 7 live platforms per topic, including Reddit, YouTube, Google News, podcasts, Substack, Medium and Hacker News, and adds your own proprietary data. A typical article draws on about 10 sources.
How do you make sure every claim is sourced?
Every finding becomes an evidence card with a claim, a quotable line and a live source URL. Each section must declare which evidence it uses before it is written, and a claim with no source URL does not get made.
Is every article checked before it publishes?
Yes. Every draft is scored on the 5 pillars and 17 checks of AEO Rank before it publishes. Our bar is 70 or more, and you can see each article's score in Studio.
Can I use my own data in articles?
Yes. Your proprietary data and first-party knowledge feed the same evidence library as the web research. A number with a sample size that no one else has is exactly what AI engines quote and name you for.
Why does original data matter for AI citations?
AI engines weigh sources by trust, and proprietary data and first-hand expertise sit at the top. If a paragraph could appear on a competitor's site with the brand name removed, it gives AI no reason to name you.
From the blog
The latest from our content engine.
Original-data articles, case studies, and AEO research from our content engine - the same pipeline we run for clients.
How we write AEO articles with AI: 3 gates before anything publishes
A trustworthy AI content workflow means that evidence is locked before drafting, because answer engines such as ChatGPT and Perplexity cite specific, clear claims, and a model without fixed facts supplies neither.
The content-ops model that keeps AEO articles citable at scale
The score-create-measure loop is a three-stage content-ops framework that keeps AEO article citation rates stable at publishing volume. Stage one (Score) runs an AEO domain audit to identify MISS queries and weak citation criteria before any brief is written.
The content edits that moved our pages into AI Overviews
See the content AI is citing without you
A free audit shows the exact prompts where AI names a competitor instead of you - the gaps the Content Engine fills with sourced, original data. Named in AI answers in 100 days, or we work free until you are.