Kanlet

Kanlet is a semantic context layer for enterprise AI. It turns a company's data and institutional knowledge into one governed semantic model so that AI agents understand business definitions, metrics, relationships, rules and exceptions, and resolve the right table, join and definition before answering instead of guessing. It is aimed at data and analytics leaders whose AI pilots stall because agents lack business context. The platform rests on three layers: a metadata graph that maps every data source, connecting tables, columns, glossary terms, dashboards and policies into one queryable structure; a memory layer that captures decision traces, recording what was decided, who decided it and why, so later agents inherit what earlier ones learned; and a knowledge graph that encodes ontology, glossary and lineage. Kanlet guides teams through capturing shared meaning, encoding it in a semantic model that can be refined as new questions arise, and governing it with classification, access control and audit trails. The context is then delivered to agents that understand, reason, route and act across CRM, ERP, ticketing, communication and analytics systems. Kanlet does not publish pricing. There is no public pricing page, and the site directs buyers to book a demo, so pricing should be treated as quote based. Kanlet argues that grounding agents in shared context also lowers token costs and speeds up answers, since agents spend less effort searching for the right data before responding.