01
Content refresh
Update pages that are slipping in AI answers before competitors take the slot.
UX Report
Product · Agents
Agents that win citations — not just drafts
Automate Answer Engine Optimization so your brand shows up more often in ChatGPT, Perplexity, and other AI answers — with less manual grind.
Agent run · content refresh
Research
- Gap: “best CRM for Series B”
- Cited: competitor docs ×3
- Your page: not mentioned
Create
- Brief + FAQ section drafted
- Tone: Brand Model locked
- Status: awaiting approval
Measure
- Published to CMS
- Re-check: 12 prompts
- Citation recovered on 4
The loop
From gap to cited content — under your rules
Agents don’t start from a blank prompt. They research what AI already cites, create to those signals, ship with approval, then measure whether citations moved.
01
Find the gaps
Surface topics and buyer questions where your brand is missing from AI answers.
02
Study what AI cites
See which pages and formats answer engines already recommend — and why.
03
Research competitors
Map rival sources and the proof patterns that win mentions.
04
Create AEO-ready work
Draft briefs, articles, and FAQ sections tuned for people and machines.
05
Refresh what slips
Update pages that are losing positions or citations before the gap widens.
06
Stay on-brand
Ground every draft in your tone, rules, and knowledge base.
07
Human approval
Route work for review — you control what gets applied.
08
Publish to CMS
Ship approved material directly into your content system.
09
Measure & improve
Track whether AI cites the new work — and feed results into the next run.
Why not a writing tool
AEO processes — not chatbots
Ordinary AI writers begin with a prompt. UX Report agents begin with what answer engines actually cite — then prove whether the work earned mentions.
Typical AI writer
- Starts from a blank prompt
- Optimizes for readability alone
- Stops when the draft looks good
- No citation feedback loop
UX Report Agents
- Research live AI citation signals first
- Create for people and recommendability
- Approve → publish → re-check answers
- Use results to sharpen the next piece
Templates
Four ready scenarios — or build your own
Start from proven AEO jobs, then customize. No engineering required.
02
FAQ generation
Ship AEO-optimized FAQ sections that answer the questions models already ask.
03
Competitive research
See who gets cited instead of you — and what evidence patterns they use.
04
New articles
Create original pieces aimed at the prompts and formats that win recommendations.
Builder
Drag-and-drop your own process
Compose research, reasoning, approval, and publish steps visually. Templates get you live fast; the builder lets marketing own the workflow — no code.
- Start from a template or a blank canvas
- Wire scrape, scorecard, LLM, and delivery nodes
- Keep approval gates where your team needs them
- Land Opportunities ready for Place → Deploy
Canvas preview
Start · Monitor gap
Buyer question missing citation
Scrape + scorecard
Live page · content readiness
Generate + finalize
On-brand draft under Brand Model
End · Opportunity
Approve → Place → Deploy → re-check
Questions
What is AEO?
Answer Engine Optimization — making your brand clearer for people and more recommendable in AI answers from ChatGPT, Perplexity, and similar systems. Agents automate that process end to end.
How is this different from ChatGPT writing for me?
A chat draft starts from your prompt. Agents first research what AI platforms already cite, create against those signals, route for human approval, publish, then measure whether citations moved.
Do agents publish without review?
No by default. Content goes through human approval under your rules. You choose when a step can run autonomously.
Can we build custom workflows?
Yes. Use the drag-and-drop builder to compose your own AEO process — or start from the four ready templates and adapt.
Do you guarantee #1 in ChatGPT?
No. Independent models choose answers. Agents improve the work you ship and re-check whether recommendations moved — honest before/after, not fake control claims.
Put AI recommendation on a closed loop
Detect gaps. Create what answer engines cite. Approve, publish, and prove it worked — with less manual labor.