Social
Views, retention, shares and comments per version and platform.
Platform signalEvery video becomes a family of answers: an article that answers the questions people actually ask AI, an FAQ, chapters and clips, all published in formats AI engines can read and cite.
Image, sound, speakers, products, on-screen text.
Everything said and shown becomes organised knowledge, tied to the exact second.
On your site, your subdomain via a connector, or ours, in the formats LLMs read.
Which page was cited, by which LLM, for which question.
Because everything starts from the video itself, every answer stays connected to its source: the article quotes the exact moment, the moment carries the proof, and the citation leads back to you. One unbroken chain, from your master to the AI answer.
Measurement methodology varies by engine: see our Methodology
Views and retention per version, citations and sentiment per engine, visits and conversions: Aive links every result to the source video, without adding up signals that do not say the same thing.
Views, retention, shares and comments per version and platform.
Platform signalMentions, citations, sources and sentiment, on a question panel and period.
Protocol observationSessions from identifiable AI referrers, separate from crawls and citations.
Observed visitLeads, sales and first-party events, under a declared attribution model.
Declared attributionCitation ≠ click · referral ≠ causality · a linked conversion alone does not establish incremental effect. Demo data in the previews.
Every module shares the same source and the same log; GEA adds ad formats designed for AI answers.
Your visibility in AI answers, measured: share of voice, cited sources, sentiment.
Your videos become citable sources: articles, FAQs, chapters and a Content Graph.
Your media, on your domain: articles, clips, Player and Aive Expert.
Optimizations applied to your pages, without a developer in the loop, reversible.
An agent that prepares and executes, reusable workflows, SSO and API.
Ad formats designed for AI answers, under governance.
The Aive GEO agent reads your AI visibility data and your videos, answers with the figures and their sources, suggests priority actions and runs workflows. Nothing is published without your approval.
How can I improve my brand’s AI visibility?
Your brand is cited in 31% of tracked answers, up +4.2 pts over 7 days. ChatGPT and Perplexity mostly cite your product videos.
Workflow started · awaiting approval
We create the source material directly from multimodal video analysis.
Beyond words, 25 models linking image, audio, entities, sourced statements and timestamps.
Renting attention is not owning an asset; we build a durable, indexable knowledge graph you keep.
The platform always separates what was observed, what is interpreted, what is recommended, what was approved and published, and what is actually measured.
Starter plan (€390 incl. VAT), AI credits included; AI Copilot and the Aive GEO agent in every plan. The four plans, add-ons and credits are detailed on the Pricing page.
One domain, an instant estimate, no account. For a dated measurement, the GEO Audit.
Monthly credits reset; pack credits stay valid while the contract is active.
Yes: the free check gives an instant preview, and a scoped GEO Audit measures your position on agreed questions, engines and markets.
First article in minutes; first measured citation typically 2 to 4 weeks, depending on LLM indexing. No citation is guaranteed.
For production and monitoring, yes; for brand strategy, no.
This video introduces the shift to answer engines. Aive helps make source material, moments and related content easier to find and verify; it does not guarantee a citation.
This loop presents the move from keyword search to answer engines. Aive links a source video, its moments, related content and observed answers within a defined scope. It does not promise a citation.
This video concludes the journey: start with authorised content, structure it, have it reviewed and observe what happens after publishing. Results depend on the corpus, configuration and measurement method.
This loop summarises the Aive chain: the source video is analysed, structured into content and experiences, then connected to observation within a measured scope. Teams approve each relevant step and no outcome is guaranteed.