GeminiWe track and improve how answer engines and AI agents describe your brand across every model your market uses. AEO, GEO and Agent Experience for brands and agencies worldwide.
Tell us who you compete with and we will run your first scan. Then we fix what AI engines and agents get wrong about your brand
How often each brand appears in AI generated discussions
| Brand | VisibilityThe share of AI answers that name the brand. | SOVShare of voice: the brand's slice of every brand mention. |
|---|---|---|
| 1Ethereum | 34% | 9% |
| 2SolanaYou | 25% | 12% |
| 3Base | 20% | 4% |
| 4Arbitrum | 18% | 6% |
| 5Polygon | 17% | 4% |
| 6Optimism | 15% | 6% |
| 7Avalanche | 14% | 5% |
| 8Sui | 13% | 4% |
| 9Aptos | 13% | 5% |
| 10Near | 12% | 3% |
For 25 years, SEO told us how we ranked. Now companies also need to know how AI sees them.
Track your visibility across AI answers. See where you rank and where you don't.
Get early access →Manage all your AEO clients in one place. Share automated, client-friendly reports that keep everyone aligned.
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How often you appear when your market asks. Measured across the prompts buyers actually type, not the ones you already win. Split by model and by language.
SHARE OF ANSWERS
Where you land inside the answer. The first protocol named, or the one mentioned after the recommendation is already made. This is what tells you which prompts are winnable.
RANK INSIDE THE ANSWER
How the model frames you. In Web3 this is the one that costs money, because a model that hedges on your bridge security loses the reader before your docs ever load.
TRUST, SECURITY, AUDIT LANGUAGE
Bring your own or start from a generated set built around your category. Payments, staking, bridging, custody, whichever question decides your deals.
Benchmark against the protocols competing for the same prompt. Positions shift weekly, so the gap is a moving target.
Models keep citing the same handful of docs sites, aggregators and forums. Knowing which ones is the difference between guessing and shipping.
Pick the engines your buyers open and the regions you sell into. Every combination is measured separately.
Each week you get a short list of what to change, with the citation data that justifies it.
Every prompt reruns daily on every model you track, so a trend is a trend and not one lucky sample.
CONNECT
Name your protocol, your domain and the competitors you care about. No code, no tag on your site.
PROMPTS
Choose the prompts your buyers ask. Start from the category set or write your own.
MEASURE
Every prompt runs on every model you selected, every day, in each market you track.
ACT
Take the ranked list, change the docs and the sources behind it, then watch the next run.
Presence by model and prompt
SAMPLE DATA, SHOWN TO ILLUSTRATE THE VIEW.
Which L1 for payments
Safest bridge 2026
fastest bridge to arbitrum
who supports staking rewards
lowest slippage dex
which wallet is most secure
Answer Engines Tracked
Languages And Market
Web3, Understood
Track your brand visibility, sentiment and position across every major answer engine; updated daily, split by model and prompt.
Know whether the model recommends, qualifies, or dismisses you and see exactly which sentence is doing the work.
Build your own prompt set from real buyer questions, or start from a category template.
AI-suggested prompts with estimated search volume help you focus on the questions that drive the most visibility.
Add rivals and see how they rank in the same AI answers. Spot the gaps worth closing and the prompts you can win.
Pick the answer engines your market uses; from ChatGPT to Grok, and set your tracking frequency per model.
See which domains AI cites most in your category, then follow platform recommendations to close the gap, from UGC to editorial.
Clean exports for ad hoc reports and quick shares.
Every project into a client ready dashboard through the connector.
Automate reporting and pipe visibility into your own systems.
Serve live data to Claude and any other agent you run.
Thanks to @lanesra_ai, we know what answers our ICP see when asking their agents about digital asset security and compliance. With Lanesra now part of our GEO pipeline, we know where @hackenclub is placed in AI overviews, who cites us, and how to get ahead of our competitors. Ultimately, we now have clear visibility of GEO issues and a path to their remediation in AI overviews and agent replies.
Great to see Hacken using Lanesra to understand how AI presents their business and where to improve. An example for the Polish ecosystem as we build towards Colosseum: solve a real customer problem and deliver value 🇵🇱
With Lanesra, we can see how AI presents Paybis when people ask where and how to buy crypto. We can track whether we appear in recommendations, how we’re compared with other platforms, and which sources shape those answers. That gives our team a clearer view of the gaps in our AI visibility and where to focus our GEO efforts.
One plan. Pick your prompts, models and projects; upgrade whenever you grow.
Company Plan
Monthly Prompts
€150/moexcl. VAT
4 models • 2 projects • 160 prompts / mo
€1,500 billed once a year, excl. VAT
Get startedIncludes a 3-day free trial.
Pay by card, SEPA Direct Debit or bank transfer.
Choose from these core models
Need more models?
Claude, Grok, DeepSeek, Qwen, Moonshot AI and Mistral are available as custom add-ons. Book a call →
Same on every option. Only prompts, models and projects scale.
Included on all options
Custom - talk to sales
Add your brand and domain, choose the markets and languages you sell into, and Lanesra builds a starter set of prompts from the questions your buyers/users actually ask. Your first scores land the same day, broken out by model and language, so you can see where you already surface and where a competitor owns the answer instead. We're onboarding Web3 teams first, so the starter prompts and sovereign-model coverage come tuned for protocols, chains, exchanges and wallets out of the box.
Every prompt re-runs daily on each model you track, so your trend lines stay genuinely comparable day to day, real movement, not an artefact of when you opened the dashboard. That cadence matters most in Web3, our first focus industry, where a token launch or protocol upgrade can change how models describe you within a week.
Yes. Every prompt can carry tags for persona, funnel stage, market or product line, and you can filter the whole dashboard by model, country and language. That lets you ask narrow questions, how first-time buyers in the UAE see you on ALLaM in Arabic versus developers in Germany on Claude in English, without exporting anything.
A mention is when an answer names you outright. A citation is when your own content shaped the answer even without naming you. We track both, because they tell you different things: one shows a model recommends you, the other shows it trusts your material enough to build its answer on it.
We separate two signals: when your content is used (it informed the answer) and when it's cited (your URL is named). You can drill from the domain level down to individual URLs with how often each gets pulled, so for a Web3 project you see exactly which docs, audits or third-party sources feed the answers in your category, and where to earn your next mention.
Increasingly it isn't a person asking; it's an autonomous agent reading your docs, pricing and on-chain data to decide what to recommend or transact. Many Web3 sites are built in React or Next.js that agents struggle to parse, so you can lose a recommendation without ever seeing it. AX audits how ready your brand is for that: whether an agent can extract your key facts, whether your MCP and llms.txt surfaces are complete, and where an agent picked a rival because your answer was too thin.
Three ways in: a Looker Studio connector for drag-and-drop dashboards, a REST API for custom pipelines, and MCP to feed visibility straight into agents like Claude, which is also how the Agent Experience loop closes. All three stream live, so the numbers stay current instead of freezing at export.
Because the models start at a disadvantage with crypto. Their training data lags months behind your last upgrade, they routinely confuse similar token names and misattribute features, and they've absorbed a lot of skeptical coverage; rug pulls, enforcement actions, failed launches; that colours how they describe the whole category. Lanesra shows you exactly where that's happening to your project so you can correct it at the source.
Yes; that's a core reason teams pick us. Alongside ChatGPT, Gemini, Claude, Perplexity and Grok, we track the sovereign models your GCC buyers actually use, Jais, ALLaM, Fanar and Falcon-H1, and we measure Arabic answers natively rather than through translation, because a model's Arabic answer is genuinely different from its English one.
Start Here
Start a free trial. Tell us your category and we will run the first scan.
