Palantir Ontology: Turning ML Predictions into Ordinary Business Object Fields

The article explains two deployment patterns for integrating machine learning models into Palantir Foundry's Ontology—real-time function calls and batch inference—so predictions become regular fields on business objects, enabling business users to consume AI outputs without technical expertise, while highlighting governance practices like versioning, confidence intervals, and wrapper functions for safe AI agent usage.

AI GovernanceBatch InferenceBusiness Objects

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Palantir Ontology: Turning ML Predictions into Ordinary Business Object Fields

Data Integration and Governance

Jun 25, 2026 · Fundamentals

Why Is Data Modeling So Hard? Master These 7 Essential Concepts

Data modeling isn’t about creating more tables; the real challenge lies in translating business logic, relationships, and metric definitions into a stable structure, which requires mastering seven key concepts—business objects, granularity, entity relationships, fact and dimension tables, metric definitions, model layering, and data lineage and quality.

Business ObjectsDimension TableFact Table

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Why Is Data Modeling So Hard? Master These 7 Essential Concepts