Generic AEO tools are built to cover every industry, which means bigger models, broader context and far more compute on every query. You pay for all of it. Kradeos is built only for B2B software products, so our inferencing is deep, precise and efficient at every layer.

Software-specific taxonomy. Every prompt is mapped to a structured taxonomy of software categories, features and buyer types. Our models don't have to work out the context from scratch each time, so each inference needs less compute.

Semantic prompt clustering. We group prompts by meaning, not just wording. Prompts that ask the same thing in different ways are tracked together, so you're not paying to run near-identical inferences over and over.

Smart inferencing schedules. Not every prompt needs to run every day. We categorise prompts into daily, weekly and monthly inferencing, which cuts compute costs by up to 40%.

Deep, well-defined inferencing. Generic tools run broad inferencing, asking large models to figure out your market, category and competitors from scratch on every query. That's expensive and less accurate. Kradeos already knows the software landscape in depth, so every inference is precise and targeted from the start. Better answers, less compute, and the savings are passed on to you.

Same AI visibility insight, focused on the prompts that bring pipeline, at around half the price.

Generic AEO tools treat a software buying journey the same way they treat a coffee brand or a hotel chain. Software is bought differently: long shortlists, industry focus, feature comparisons, buyer types, integrations and implementation risk. Kradeos is built around how software is actually researched and bought, so every layer is sharper.

Prompts built from real buyer behaviour. Our prompts are refined using real software buyer journeys from Comparesoft, a B2B software comparison platform with nearly a decade of buyer data. You track the questions buyers actually ask AI, not keyword guesses.

Software knowledge graph. Every product, category, feature, industry and customer type (SMB, Mid-Market, Enterprise) is connected in a software-specific knowledge graph. You see exactly where you win and lose, down to the feature, industry and buyer segment.

Natural language understanding. Our NLU models read AI answers the way a buyer does, understanding intent, sentiment and context, not just counting brand names. We know the difference between being recommended, compared or dismissed.

Coreference resolution. AI answers rarely repeat your product name. They say "it", "the platform" or "this tool". Our coreference and anaphora resolution links every reference back to the right product, so no mention or recommendation is missed or misattributed.

Pattern matching across answers. We detect recurring patterns in how LLMs rank and describe software in your category, revealing which features, sources and claims consistently push competitors above you.

Mentions vs citations. Being mentioned isn't the same as being recommended. We score mention rate and citation rate separately, so you know whether AI is just aware of your product or actively pointing buyers to it.

Measure, influence, remeasure. Most tools stop at a dashboard. Kradeos closes the loop: measure your visibility, act on the gaps, then remeasure to prove what moved.

Together, these steps make Kradeos up to 6x more efficient than most generic AEO tools. Built for software products, not every product. That's the difference.