Itera launches topic cluster features for LLMO Cheki

Itera Inc. has launched new topic cluster features for its LLMO (Large Language Model Optimization) measurement and improvement tool, LLMO Cheki. The update is designed to help websites structure content to be more easily cited by generative AI search engines.

Because AI models often decompose complex queries into multiple sub-questions, sites with systematic, themed content are more likely to be referenced. The new functionality supports the entire pillar page strategy, including cluster map visualization, keyword suggestions based on search demand, and the automatic insertion of contextual internal links to connect related articles.

Additionally, the tool allows users to verify effectiveness by tracking changes in AI citations and search traffic at the cluster level rather than just for individual articles. These features are available across all LLMO Cheki plans without additional fees.