Where do you appear?
We test real buyer prompts across ChatGPT, Claude, Gemini, and Perplexity to find where your brand appears and where it is absent.
Answer Engine Optimization
Own how AIanswersabout your brand
Buyers ask ChatGPT, Claude, Gemini, and Perplexity who to trust before they ever contact sales. If your brand is missing from those AI answers, you lose deals before you know they exist. We audit your AI visibility, deliver a prioritized fix list, and track improvement weekly.
Baseline audit in minutes. Prioritized roadmap in one cycle. 50+ weighted rules across 4 signal verticals: authority, structure, retrieval, and trust.
What is AEO?
SEO gets you ranked. AEO gets you cited.
Answer Engine Optimization is the discipline of ensuring AI systems mention, compare, and cite your brand when buyers ask decision-stage questions.
Search rankings still matter, but buyers increasingly make shortlist decisions inside generated answers. AEO determines whether your brand appears with credibility at that moment.
We audit visibility, identify gaps, deliver a prioritized execution plan, and track movement across the AI surfaces your buyers actually use.
Why are you cited or skipped?
Our 50+ rule engine diagnoses the authority, structure, retrieval, and trust signals that drive AI citation decisions.
What should you fix first?
Every finding maps to a prioritized action item ranked by business impact so your team acts on what matters most.
How do you track progress?
Weekly retests measure movement. Monthly reviews align teams. Quarterly resets refine strategy and budget allocation.
Scoring model
One strategic score for visibility health
We apply weighted signals across 50+ rules spanning authority, structure, retrieval, and trust, then normalize to a 0-100 index so leadership can track performance across pages, clusters, and reporting periods.
Scoring formula
AEO Score=Σ(rule score × rule weight)/Σ(max score × rule weight)× 100
Authority Tier
Strong alignment across all signals
Strong visibility architecture. Content, trust, and retrieval systems are aligned across high-intent prompt clusters.
Growth Tier
Foundational systems with uneven coverage
Foundational systems are in place, but citation consistency and answer readiness are uneven across models.
Recovery Tier
Structural gaps and unstable visibility
Partial coverage with meaningful structural gaps. Prompt-level visibility is unstable and easy to displace by competitors.
At-Risk Tier
Weak signals with high commercial risk
High commercial-risk posture. Core discoverability, trust, and retrieval signals are too weak to sustain AI citation share.
50+ rules across 4 signal verticals give leadership a credible, repeatable baseline.
Strategic outputs
What your team gets beyond a score
Not another dashboard. An execution-ready operating lane that converts AI visibility diagnostics into measurable commercial outcomes.
Rule-by-rule diagnostics
Each page is evaluated against 50+ weighted rules spanning authority, structure, retrieval, and trust. You see per-rule scores, not a single opaque number.
Answer Rate tracking
We run real buyer queries across ChatGPT, Claude, Gemini, Perplexity, and more, then measure how often your brand is cited. That percentage is your Answer Rate.
Ranked execution backlog
Every finding converts into a prioritized action item with estimated impact, making it clear what your team should fix first and why.
Governance-ready reporting
Weekly performance snapshots, monthly alignment reports, and quarterly strategy reviews keep leadership and execution teams on the same page.
Executive overview
One system for visibility, trust, and revenue impact
Replace disconnected SEO and AI experiments with one measurable operating lane that connects AI visibility to qualified pipeline.
See where you show up
Find out which AI prompts mention your brand, which ones skip you, and where competitors appear instead.
Understand why AI cites (or skips) you
Diagnose weak trust signals, missing references, and content gaps that cause AI models to leave your brand out.
Get a prioritized fix list
Receive a ranked action plan covering content, technical SEO, and authority building so your team knows exactly what to do first.
Test across every major AI model
We check your visibility on ChatGPT, Claude, Gemini, Perplexity, and more simultaneously, not just one model.
Evidence
Evidence built for decision confidence
Benchmark data, repeatable measurement, and practical diagnostics show teams what is moving, what is stalled, and what to prioritize next. This gives leadership a clearer signal for where execution effort should go first.
Prompt coverage
Visibility across high-intent buyer questions. This shows whether your brand is present in the moments that influence shortlist decisions.
Citation quality
Source strength and model trust behavior. Stronger citation quality improves confidence in your positioning across answers.
Competitive risk
Gaps that reduce shortlist inclusion. Left unresolved, these gaps let competitors shape buyer perception earlier in the cycle.
What a typical engagement measures
Targets vary by category and starting point. These are common focus areas.
| Metric | Baseline | Target |
|---|---|---|
| AI prompt coverage (are you mentioned?) | Low | High |
| Citation consistency across models | Inconsistent | Stable |
| Qualified pipeline from AI traffic | Untracked | Measured |
Cadence over guesswork
Teams running consistent prompt retests outperform ad-hoc optimizers because movement is measured, not assumed.
Intent-first execution
Mapping high-value prompt intent before production reduces wasted publishing and concentrates effort where buyer demand is real.
Cross-model consistency
Visibility on one model does not guarantee visibility on others. Simultaneous testing reveals gaps single-model audits miss.
Reference frameworks: NIST AI RMF Playbook, OECD AI Policy Observatory, Stanford HAI AI Index, arXiv: LLM Citation Bias, and arXiv: AEO & Generative Search.
Impact
Why this matters for revenue
AI answers shape buyer decisions before your team enters the conversation. Visibility in AI is now a revenue variable that compounds when governed as one system.
Appear when buyers ask AI
When prospects ask AI to compare solutions, your brand appears as a credible option instead of being left off the shortlist.
Win trust before the first call
Prospects arrive pre-informed about your strengths because AI already cited your brand during their research.
Connect visibility to revenue
Track which AI-referred visits convert into qualified pipeline so you know exactly where content investment pays off.
Outpace competitor positioning
When competitors appear in AI answers and you do not, they shape the shortlist before your team is contacted.
What leadership should track
Three KPIs reveal whether AEO is moving business outcomes: Answer Rate, citation quality, and pipeline attribution.
Answer Rate
What percentage of relevant AI prompts cite your brand? This is the core metric we track.
Measured weekly across multiple models
Citation quality
Are AI models citing your best pages, or outdated/weak content? We flag which sources need strengthening.
Evaluated across multiple signals
Pipeline attribution
Which AI-referred visits turn into leads and pipeline? We help you set up tracking so you can see the connection.
Cadence tuned to business goals
Method4-step cycle
Operating method and methodology
A repeatable cadence from baseline diagnostics to prioritized execution and accountable governance. The sequence below mirrors how teams plan, execute, and review progress each cycle.
Execution flow
Map prompts, score visibility, prioritize fixes, and retest in one accountable loop.
01
Map buyer prompts
Identify the buyer prompts that drive evaluation and shortlist decisions.
02
Audit current visibility
Score pages against citation signals to reveal where you win, lag, and why.
03
Deliver prioritized fixes
Turn gaps into a ranked backlog across content, technical SEO, and authority.
04
Measure and iterate
Retest weekly across models and iterate until inclusion becomes consistent.
Framework coverage
Each pillar defines what to improve and why it affects citation outcomes.
Authority
Credibility and evidence quality
Strengthen credibility with high-quality evidence, attribution patterns, and defensible claims that AI models rely on.
Focus: Citation trust
Structure
Semantic clarity and content flow
Improve content organization and retrieval readiness so models can extract and cite your content accurately.
Focus: Model parseability
Retrieval
Prompt coverage and capture
Increase coverage across commercial prompt clusters and improve answer capture consistency over time.
Focus: Answer inclusion
Trust
Factual alignment and safety
Monitor factual accuracy, confidence quality, and policy-sensitive surfaces before they erode brand trust.
Focus: Quality assurance
What this means in practice
Your team receives a weighted rule-by-rule backlog with per-page diagnostics, improvement suggestions, and a weekly retest loop showing where gains compound and where progress stalls.
About us
We help brands get cited by AI.
Our team combines search strategy, content diagnostics, and structured execution to help you understand where you stand in AI answers and what to do about it.
50+
Weighted rules across 4 verticals
ChatGPT · Claude · Gemini · Perplexity · more
AI models tested simultaneously
Adaptive
Testing cadence by business need
FAQ
Frequently asked by enterprise teams
Clear answers for leadership, growth, and operations teams evaluating AEO as a revenue system.
Contact
Start with your priority
Share your revenue-critical gap and we will respond with a practical baseline path and execution scope.
Contact channels
Share goals, constraints, and timeline. We will reply with practical next steps.
General inquiries
Platform coverage
ChatGPT · Claude · Gemini · Perplexity · and more
Engagement style
Assessment · Prioritization · Execution advisory