Enterprise AI projects fail at alarming rates because AI can't understand your data. ARAMAI changes this by transforming hidden schemas into visible, governable intelligence that both humans and machines can use effectively.

Your data schemas exist everywhere—trapped in thousands of integration points, invisible to business teams, inaccessible to AI systems. When AI has to guess instead of know, you get weeks-long change cycles and 70% validation failures. We solve this fundamental disconnect.

CoreModels fetches schemas from any system, builds intelligent semantic mappings, and creates a unified hub where business teams directly govern data definitions while AI agents query authoritative structures in real-time.

Our vendor-agnostic methodology works with your existing infrastructure—bring your own graph database, semantic stack, or schema language (JSON-LD, JSON Schema, RDF, XML, and more). The Schematica suite amplifies this through RealContent (seamless Figma integration), ContentFlow (advanced conversational design), and SchemaFlow (effortless Schema.org modeling).

Community for Data Model Sharing: The Schematica Schema Library creates the first marketplace for schemas. Data Models, Content Models, Semantic Models. Organizations share production-validated models instead of recreating identical solutions—like GitHub for data schemas and other knowledge models.

The results: AI validation success jumps from 30% to 98%, integration redundancy drops 70%, and schema changes compress from weeks to hours. Built on five years of R&D, our graph-based architecture preserves critical business context while making enterprise data truly AI-ready.

The technology has been proven with major institutions across health sciences, pharmaceutical research, biomedical informatics, technology platforms, and financial services. Ready to turn your data from AI's biggest obstacle into its greatest strategic asset?

ARAMAI

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ARAMAI

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