Buyers no longer start on your product page, they ask an LLM. Klariton measures how ChatGPT, Perplexity, Gemini and Claude answer early buyer-intent questions in your category, shows where competitors win and your brand is missing, and turns each gap into concrete content, BIQs and product-data actions.
Buyers begin with a problem, not a product name. The LLM answers the early question and builds the relevant set before anyone visits your shop. If you're not in that answer, you're out of the decision before it starts.
Every metric is a count of citations, answers and sources, per engine and per buyer phase. No blended index. Figures below are illustrative demo data; in the product they show your real numbers.
LLM discovery shapes the relevant set most where the decision is considered. Klariton is built for categories where buyers research a problem before they know the product, clear targeting, not a claim of fit for everything.
Honest scope: if buyers don't research, there's little discovery to win, and we'll say so.
This is the core of Klariton: a closed loop from LLM scan to attributed impact. Every output is created or recommended, reviewed, and approved by you, never published on its own.
Queries and answers captured per engine and intent phase.
→Brand missing or a competitor cited, gap classified by type.
→The matching knowledge action is created or recommended.
→Source-backed and checked for claim drift before anything ships.
→The approved answer appears in the advisor, on product and in the magazine.
→Clicks and order signals are traced back along the chain.
Early questions want orientation; late ones want a decision. Klariton routes each gap to the surface that fits its intent phase, and links them into a cluster, so problem content reaches product without reading like an ad.
Source-backed buyer questions right on the product, for buyers close to choosing.
Compare · DecideGuides on problems and solutions, the answer the LLM looks for in the early phase.
Discover · ExploreConnected articles around one buyer problem, depth single pages can't deliver.
Problem-aware · Solution-awareEmbedded answer and recommendation blocks exactly where the purchase happens.
Buying contextKlariton does not act on its own in your shop. It measures, explains and suggests, you stay in control.
Klariton changes nothing in prices, stock or content without your approval. The scope is clearly defined and traceable, not a black box.
Every output is built from approved material and checked before it's published. Unsupported claims and claim drift are flagged before they go live.
Data is hosted in the EU and minimized and protected before model processing. The architecture is designed for the requirements of the AI Act, trust by default.
Klariton connects visibility to impact: from the first LLM read, through the closed gap, to the product click. A traceable measurement chain, we track impact, we don't promise it.
The LLM answers an early buyer question in your category.
Your brand is missing or a competitor is cited.
Klariton closes the gap with source-backed, LLM-readable content.
The answer appears in the chat advisor, on product and in the magazine.
Product click and order signal are mapped back to the chain.
One scan shows your LLM discovery gaps across all four engines. It turns into a concrete content and BIQ plan, controlled, source-backed, approval-gated.