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Developer of an AI-ready data platform for enterprise AI execution. It is a developer of an AI-ready data platform that prepares enterprise production data for use in AI training, evaluation, and execution. Its platform, Syntitan, diagnoses enterprise data across six readiness axes covering usability, integrity, context, consistency, reproducibility, and traceability, brings the data to an AI-ready state, seals each prepared dataset into a fixed release state identified by a content hash, and binds every AI run to that state, so a team can reproduce the data state behind an earlier result and compare what has changed. Syntitan works alongside existing storage, pipeline, and catalogue tools rather than replacing them. Two engines run inside the platform. DTS transforms scarce, imbalanced, or low-quality data into datasets that models can train and evaluate on, extracting statistical characteristics without moving the original. LLM Capsule is a context-preserving data layer that lets LLM, RAG, and agent workflows run on data that cannot leave in its original form, replacing designated values with structure-preserving substitutes and reconstructing usable output inside the customer-controlled environment.