GEO · Generative Engine Optimization

World's only AI visibility platform, built on a research-grade optimizer.

Scan, monitor, and win AI answers across ChatGPT, Claude, Gemini, and Perplexity — with an optimizer engine that rewrites pages rule by rule and proves the lift. Not another "add an FAQ" tool.

tracked across gpt-5 claude gemini perplexity
app.aiseop.ai/visibility/geo-score
AISEOP GEO Score dashboard — per-page AI-readiness scored across engines
Live GEO Score · every tracked page, every engine
Founding partners · by invitation We're onboarding a select group of founding partner agencies with direct access to the team.
The problem

Your buyers now decide with AI

and right now, that answer is written without you in it.

? "what's the best platform for enterprise teams?"
For enterprise teams, a few platforms stand out. Competitor A has the broadest feature set, while Competitor B is known for strong reporting. Competitor C is often recommended for fast-moving teams that want deep integrations out of the box.
✕ Your brand — not mentioned. The decision already happened, and it never touched your analytics.

This is a fundamental shift in how buyers discover you — and AISEOP makes sure you're part of it.

Content Optimization · our sharpest edge
◆ Flagship module

Make every page quotable.

The Optimizer takes the content you already have and rebuilds it for citation — restructuring entities and tightening factual density on every existing page. A structured, tested method, not a hunch or a rewrite button. Each improvement measured before and after, per engine.

app.aiseop.ai/optimizer
AISEOP Optimizer — structured content blocks, live preview, and GEO score lift per rewrite
Optimizer · block-level structure, live preview, and measured score lift
Before · readiness 41 After · readiness 87 ▲ +46
← drag to compare →
Our platform helps businesses leverage AI for growth and competitive advantage. We offer enterprise-grade solutions that drive digital transformation across marketing, sales, and operations teams.
AISEOP rewrites your pages for ChatGPT, Claude, Gemini, and Perplexity citations — using entity-structured content, Schema.org markup, and factual density that large language models actually quote in product comparisons.
Readiness
41
/100
+ Schema.org markup + Entity coverage (4 → 12) + Factual structure
Why it's different
Other tools just ask ChatGPT what to fix. We built an engine.
A typical AI-SEO optimizerGeneric advice
?"Add an FAQ section to your page."
?"Use more keywords in your headings."
?"Write a longer meta description."
?"Add internal links to related content."
Ruleset
None
Scoring
None
Proof it moved
None
The AISEOP optimizer engineRule audit
A·11entity_definitionFAIL→FIXED+6
B·02structured_data_coverageFAIL→FIXED+9
C·04claim_specificityWEAK→FIXED+5
D·07comparison_structureFAIL→FIXED+8
…rest of the weighted ruleset, checked block by blockreadiness 41 → 87
Ruleset
Weighted, 4 categories
Scoring
Per block, per engine
Proof it moved
Re-scored: 41 → 87
Optimizer

Paste a URL. Get AI-ready rewrites with tracked improvements — sentence by sentence, tested against live prompts. Every recommendation traces to a specific rule, not a hunch.

Generator

Produce AI-ready articles from a brief. Schema markup, entity coverage, and citation-friendly structure built in by default — the structural signals answers are built from.

Before/after impact tracking

Every optimization tracked against its baseline. See which rewrite moved which engine. Re-score in one click — loop closes in minutes.

Optimizer Generator Impact tracking
app.aiseop.ai/content-optimization
AISEOP Content Optimization dashboard — AI readiness score, optimized pages, and generator output
Optimization dashboard · readiness score, pipeline, and lift per rewrite
01 · Structured
Every page, broken into blocks
Headings, entities, claims, and schema are pulled apart into discrete, scorable units — so nothing is optimized by feel.
02 · Tested
Every change is re-scored
Each rewrite is measured by its GEO score before and after. If it doesn't move the score, it doesn't make the cut.
03 · Engineered
A repeatable pass, not a one-off
The same rigorous pipeline runs on page one and page ten thousand — consistent, measurable, and reproducible every time.
Visibility

Where you stand, right now.

Full access audit, per-page AI scoring, and a single number that tells you exactly how visible you are — across all four engines at once. The diagnosis before the cure.

Crawl & access audit

llms.txt, robots.txt, schema.org coverage scored across every page. Know exactly what AI crawlers can and can't see.

GEO Score across 4 engines

One number to know if you're winning. Benchmarked against your industry average, updated on every crawl.

Simulation

Predict tomorrow's answer before you ship. Run prompt simulations against staged content — no more surprises post-publish.

Access & Crawl GEO Score Simulation
app.aiseop.ai/visibility/simulation
AISEOP Simulation — ask any LLM a question and see who it cites, where you rank, and what it said
Simulation · see who an LLM cites before you publish
AI Monitoring

Every mention, the moment it happens.

Once you're cited, we watch what comes next — every mention, per engine, per competitor, as it appears. The missing layer of your analytics stack.

Every mention, captured

Every instance your brand appears in AI answers — across all four engines, all day, every day. Never miss a citation again.

Share of voice vs. competitors

See your slice of AI mindshare, per engine, against up to 10 competitors — updated daily.

Citation-level traffic attribution

Tie every citation back to a session. Finally know which LLM sent the visit — the missing layer of your analytics stack.

Citations Share of Voice Attribution
app.aiseop.ai/ai-monitoring
AISEOP AI Monitoring — citation volume, share of voice, trending prompts, and LLM traffic sources
Monitoring · citation volume, share of voice, and LLM traffic, live
The closed loop

Score it. Optimize it. Get cited. Then run it again.

AI visibility isn't a task you finish — it's a loop you run.

The Rule Engine · our real edge

The rules of AI citation keep changing. So does our engine.

Our Rule Engine is built on two layers. First, we track how the AI models themselves evolve and derive our citation rules directly from how LLMs read, rank, and quote sources. The engine is designed as a closed loop: as founding partners deploy fixes, real citation outcomes feed back into rule weights. The model layer tells us what should work; the real-world layer proves what does — together they land on a far more accurate result than either alone.

Built on published research
Every rule in the engine derives from peer-reviewed research on how generative engines retrieve, rank, and cite sources — a corpus of scientific work we've been collecting, dissecting, and testing since 2024.
From the current ruleset
A-11entity_definition
A-23claim_evidence_pairing
B-04answer_block_structure
B-17citation_anchor_density
C-02schema_entity_alignment
Names only — full definitions, weights, and scoring live in the engine.
01 · Develop
Derive rules from the models
As the AI models evolve, we study how LLMs actually read, rank, and quote sources — and engineer citation rules straight from that behavior.
02 · Apply
Deploy to every page
The current ruleset ships across founding partners' pages — scored and optimized the same way for every page on the platform.
03 · Measure
Add the real-world layer
As founding partners deploy fixes, real citation outcomes flow back — which pages got cited, across ChatGPT, Claude, Gemini, and Perplexity — the ground-truth layer on top of the model.
04 · Learn
See what moved the needle
We compare rules against aggregated results — which lifted citations, which didn't. Winners gain weight, weak ones retire, then we develop the next batch.
Two layers, one engine: how the models work, proven by what happens in the real world. Like reinforcement learning, we never stop tuning the ruleset — methodical, scientific, and improving for everyone on the network at once.
Rule changelog · continuous calibrationlast 30 days
PROMOTED
New citation signal moved to production. Validated in backtesting across all four engines before it shipped.
A · 17
RECALIBRATED
Signal weights rebalanced. Retuned after a model update shifted what answers reward.
B · 04
DOWN-WEIGHTED
Low-signal heuristic reduced. Regression showed it no longer predicts whether a page gets cited.
C · 09
DEPRECATED
Legacy signal retired. Pruned from the engine — zero measurable lift in the current dataset.
D · 02
For agencies · our beachhead

Run GEO across every client, from one workspace.

AISEOP is built first for the agencies bringing generative-engine optimization to their clients. Manage every brand in one place, report in your own colors, and give each teammate exactly the access they need.

Multi-brand workspace

Every client in one dashboard — separate scores, prompts, and citation feeds, switchable in a click. No juggling logins.

White-label client reporting

Send GEO reports under your own brand — your logo, your colors, your domain. The insight is ours; the credit is yours.

Role-based access

Owners, strategists, and clients each see the right view. Grant per-brand permissions without exposing the whole account.

Multi-brand White-label Role-based access

In-house on a single brand? AISEOP works for you too — the same workspace, scoped to one domain.

Agency workspace Sample view
Client brands · GEO Score
acme.com
73
northwind.io
58
vertex.ai
41
lumen.co
66
4 brands · role-based access White-label ✓
The method

No black box. Every step is a real part of the platform.

Three moves, one loop — and each maps to a module you can open right now. Measure, optimize, track. Nothing hand-wavy, nothing hidden.

01
Measure

See exactly where you stand in AI answers today — scored across GPT‑5, Claude, Gemini, and Perplexity in a single pass.

→ Visibility
02
Optimize

Apply the exact changes with the Optimizer — structured, tested rewrites, each traced to the rule it fixes. Never a hunch.

→ Optimizer
03
Track

Watch new citations appear and re-score to confirm each change worked. The loop closes — cause and effect, not a black box.

→ Monitoring
Onboarding

Integrated in seconds — here's how.

Connect a domain and you're live in four quick steps. No engineering ticket, no long setup call — most workspaces run their first scan in about two minutes.

01/ 04 · Domain

Add your domain.

We verify it, read your robots.txt and sitemap, and flag anything blocking AI crawlers — including a missing llms.txt — in a single pass.

◆ ~15 seconds
app.aiseop.ai/setup · step 1
Onboarding step 1 — verify your domain, check robots.txt, sitemap, and llms.txt
02/ 04 · Pages

Pick the pages that matter.

We crawl and surface every page worth tracking, tagged by type. Select the ones that count for your brand — and add more anytime from the Pages library.

◆ crawled instantly
app.aiseop.ai/setup · step 2
Onboarding step 2 — explore and select the pages you want to track
03/ 04 · Prompts

Choose the prompts you'll track.

Start from prompts we suggest for your space, or write your own. These are the real questions we'll watch across every engine, on your schedule.

◆ suggested for you
app.aiseop.ai/setup · step 3
Onboarding step 3 — pick tracking prompts, suggested and custom
04/ 04 · Scan

Run your first scan.

Choose your engines and go. Results land in your dashboard in about 30 seconds — GEO score, citations, and the exact gaps to fix first.

◆ ~30 seconds to results
app.aiseop.ai/setup · step 4
Onboarding step 4 — run your first visibility scan across engines
Free scan

Now see where you actually stand.

You've seen how it works and how fast it sets up. Point it at your own domain — we check your live site, engine by engine, and show you exactly what to fix.

scanning across gpt-5 claude gemini perplexity
Who's building this

Purpose-built infrastructure for the answer layer.

AISEOP isn't a marketing dashboard with an "AI" label bolted on. The crawling, scoring, Rule Engine, and citation tracking are engineered from the ground up for how answers actually get written. We're early — and we'd rather show you the exact mechanism than borrow proof we haven't earned. The work stands on its own.

FAQ

Questions, answered straight.

What is GEO?
Generative Engine Optimization is the practice of structuring content so AI answers — ChatGPT, Claude, Gemini, Perplexity — cite, quote, and recommend it. It's the successor to SEO for a world where the answer, not the blue links, is the front door.
What's the difference between AEO and GEO?
None that matters — they're the same discipline under different names. AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) both describe optimizing content to be cited and quoted inside AI answers. The label varies by who's writing; the work is identical, and it's exactly what AISEOP does.
Is GEO a one-time fix, or ongoing?
Ongoing. The AI models change, and what they reward changes with them — a page cited today can quietly drop out of answers after a model update. That's why the Rule Engine keeps evolving and why we re-score your pages continuously, rather than handing you a one-time report that goes stale.
How is this different from SEO tools?
Semrush and Ahrefs optimize for ranking in Google's index. AISEOP optimizes for being cited inside AI answers — a different signal set entirely. We score citability, run answer simulations, and monitor mentions across four engines, none of which appear in traditional search tools.
What makes you different from other GEO tools?
Most GEO tools optimize on hunches and recycled SEO folklore. We don't. Our Rule Engine derives every rule from how large language models actually retrieve, rank, and cite sources — and keeps re-weighting them against real citation outcomes. Every optimization we recommend traces back to a rule, not a guess.
How fast will I see results?
Your first GEO score and gap list land about 30 seconds after your first scan. Optimized pages move their readiness score immediately; new citations in live answers typically follow as engines re-crawl your updated content over the following days.
Which AI engines do you cover?
GPT-5 (ChatGPT), Claude, Gemini, and Perplexity — scored, optimized, and monitored together under one number, so you're never tuning for one engine at the expense of another.
Do you support agencies and multiple brands?
Yes — agencies are a primary audience. One workspace holds every client brand with separate scores, prompts, and citation feeds; reports go out white-labeled under your own brand; and role-based access gives owners, strategists, and clients each the right view.
Pricing

Simple pricing. No surprises.

AISEOP is currently onboarding founding partners. Plans below reflect launch pricing — reach out to get early access.

Running GEO for multiple clients? Agency and reseller plans bundle multi-brand workspaces and white-label reporting — see For Agencies.

Starter
$39
per month
  • Single domain
  • 10 tracked pages
  • 10 tracked prompts
  • 20 content optimizations or generations / month
  • Weekly monitoring run
  • 1 AI engine
Book a demo
Growth
$149
per month
  • Single domain
  • 30 tracked pages
  • 50 tracked prompts
  • 50 content optimizations or generations / month
  • Daily monitoring runs
  • GA4 traffic integration
  • 2 AI engines
Book a demo
Enterprise
Custom
custom pricing
  • Custom domains
  • Custom pages & prompts
  • Unlimited content optimization & generation
  • Daily monitoring runs
  • All 4 AI engines
  • Dedicated onboarding & support
Book a demo
Get started

Own your place in the answer.

Run AI visibility as a loop — measured, method-driven, and honest about the proof. Book a demo, or start with a free scan on your own domain.

Book a demo Run a free scan

all 4 engines · no card required to preview