For two decades, discovery meant a list. Ten blue links, judged by you, ranked by relevance. The buyer was the decider, SEO was the lever.
That is over.
Today the first question goes to an assistant. Buyers do not see a list, they see an answer. A handful of brands, named directly, presented as the considered choice.
The decision is being made in a place SEO cannot reach, by a system that does not show its work, in a moment you have no visibility into, until your pipeline starts to dry up.
Most categories do not yet have a settled answer in AI search. Priors are still forming, and a brand that becomes easy for a model to describe now is far cheaper to establish than one fighting an incumbent later.
The brands that move first will not be replaced.
The brands that wait will not be remembered.
AEO and GEO describe a goal: getting cited inside an AI answer. Neither explains why AI selects one brand over another, or what to do about it. ARI is the missing layer.
Airise is built around three intelligence layers that work continuously, not one-off reports. Map the category. Decode the signals. Execute the plan.
Queries across all seven models: ChatGPT, Claude, Gemini, DeepSeek, Qwen, Llama and Mistral using our proprietary Prompt Graph, which maps how prompt phrasing and intent shape which brands get recommended. A complete map of who gets recommended in your space, and how often.
For every recommendation your competitor receives that you do not, Airise identifies the exact AEO, GEO, and entity signals driving it. Entity signals, structured data, content patterns, and the gaps the models name themselves.
A live, prioritised action plan derived from your category's actual recommendation patterns. Not generic advice. Specific GEO content moves, AEO fixes, authority targets that move your ARI Score week over week. Each one tied to the prompts it should affect.
Every score traces back to a moment like these. Airise reads each model's answer as it lands: who it named, what it cited, and why it chose them over you. This is the layer the trackers do not keep. Not just that you lost, but exactly why.
Airise runs the whole loop. Map and decode every week, execute continuously. Your ARI Score moves week over week because your inputs do.
Every tier returns the same thing at a different scale: the sentence each model used, and what it names instead of you. What changes is how many brands, and how often.
One free report per brand. The verbatim sentence each model used to name someone else, the competitors it named, your share of voice and your ARI score. The complete report. Not a teaser.
One deep scan across all seven models. The full diagnostic, no commitment.
One brand, tracked every week, with the movement called out for you.
White-label, priced per brand. Built for running client work at scale.
Need more brands, enterprise, or MENA and Arabic-language coverage? Contact us.
Prefer annual billing? Save 20 percent, just ask.
Your client asks why ChatGPT recommended a competitor. Right now the honest answer is that nobody knows. We give you the sentence the model actually used.
We run recommendation scans across your whole client book, white-labelled, priced per brand. You keep the relationship and the reporting.
Most tools tell you whether a brand appeared. A number does not survive a client asking why.
Captured verbatim, with character offsets back to the model's own response, attributed to the model that said it and the prompt that produced it. Not paraphrased, not summarised, not scored into a single figure.
Each scan runs the same prompt set across seven models and separates branded questions from organic ones, so a mention only counts when the client's name was never in the question.
Seven models disagree with each other constantly. The disagreement is the finding, and it only shows up if you keep all seven separately.
The competitors your client names in a kick-off are rarely the ones models actually reach for. The gap is usually the most useful slide in the deck.
A single reading is a snapshot. Rescans on a fixed prompt set turn it into a record of what changed after you did the work.
The per-brand view answers a client question. The roster view answers yours: which accounts are drifting, and which are about to ask an awkward question on a renewal call.
Each client tracked on its own prompt set and its own category, reported together so the book reads as one picture.
Where a brand has gained or lost ground since the last scan, and which model moved.
Your logo, your colours, your delivery. Nothing in the client's hands says Airise unless you want it to.
A one-off single scan is $249. A single brand without the white-label layer is $199 a month. Volume terms above roughly fifteen brands are a conversation, not a published number.
Send us the roster. Client names and their sites. No commitment at this stage and no card.
We verify the category from their own copy. The category noun decides what the models are asked, so it comes from how each client actually describes themselves, not from a guess. You confirm before anything runs.
First scan on one brand, free. You see the real output before you decide anything, including the parts that are unflattering.
Then we set the roster up. Billed per brand, monthly, changeable whenever the client list changes.
Replies come from Jason, who runs Airise.
No client logos on this page and no adoption figures, because we have not earned them yet. The product is an argument about evidence, and one invented line here would undo it.
Onboarding is done by hand. There is no self-serve checkout on purpose. You email, we talk, we set it up. That caps how many agencies we can take on at once, which is the honest trade.
Nobody can guarantee a citation. Not us, not anyone selling you otherwise. We show you what the models said, and whether it changed after you acted.
A low score is a real reading, not a broken one. Some brands score at or near zero on first scan because models cannot resolve the name to a distinct entity. That is a finding with a fix, and we will walk you through it rather than hand you a bare number.
It happens, and it is a real reading rather than a broken one. A zero usually means the models cannot resolve your name to a distinct thing, so they reach for the category or a better-known brand instead. That is a describability problem with a known fix, and it is more actionable than a middling score. We walk you through it rather than hand you the bare number.
Yes. The free ARI diagnostic is a one-time scan with no commitment. You can upgrade to any paid tier at any time. Your historical scan data carries over when you subscribe.
It's coming for the Agency plan. You'll be able to generate PDF reports with your own branding, share client-facing report links, and manage multiple brands from a single dashboard. Most agencies resell ARI audits at a significant markup.
Every tier tracks all seven: ChatGPT, Claude, Gemini, DeepSeek, Qwen, Llama and Mistral. That includes the one-off Single scan. Perplexity is coming. Agency gets first access to new models as they come online. Each model is analysed independently because recommendation behaviour varies significantly across LLMs.
Yes. Annual billing saves 20% across all tiers. You can switch between monthly and annual billing at any time from your account settings.
Built to meet GDPR, UK GDPR and CCPA. Encrypted at rest and in transit, never sold or shared with advertisers or data brokers, and deletable at any time from your account. The full detail, including retention periods and sub-processors, is in the privacy policy.
Yes. A signed DPA is available on the Agency plan on request. Reach out at hello@airise.digital with your legal team's requirements and we'll send our standard DPA template within two business days.