The first step to successful AI adoption is converting data into a language AI can understand. AkasicIN collects and parses documents, logs, and system data scattered across the enterprise, transforming them into a standardized, AI-ready format for immediate use—all within a single platform.

Prepared data needs to be stored in a single repository where it can be instantly connected regardless of format. AkasicDB unifies graph, vector, and relational data into a single, seamless DBMS, enabling high-performance connections and rapid storage even for ultra-large-scale enterprise data.

Once vast amounts of data have been gathered, it is time to impose rules and semantics to govern AI. AkasicON defines the semantics and accountability of data, embeds enterprise operational policies into the system, blocks uncontrolled AI risks, and establishes the standards for operations.

On top of defined rules, AI can finally propose evidence-based judgments and executable actions. AkasicAI interprets the intent behind queries using ontology information and derives validated action plans through What-if simulations.