A modular, production-grade software architecture that integrates data, AI, and operational workflows into a unified platform for enterprise and government-scale decision-making.
Palantir Foundry's AI Mesh is a modular, production-grade software architecture that integrates data, AI, and operational workflows into a unified platform for enterprise and government-scale decision-making. It connects Palantir's Artificial Intelligence Platform (AIP), Foundry (data operations), and Apollo (software delivery) into a single composable environment.
End-user applications built using Foundry's AI and ontology capabilities; examples include supply chain control towers, defence logistics, and risk analytics.
The Ontology Layer transforms Palantir's AI Mesh from a traditional data architecture into a living semantic engine that unifies people, data, and AI under a shared operational language.
Through its Semantic–Kinetic–Dynamic architecture, the Ontology Layer not only mirrors the enterprise—it empowers it to sense, reason, and act through AI at operational scale.
Explore Ontology LayerHandle ingestion, transformation, lineage, and governance across heterogeneous sources.
Enable training, deployment, and management of AI/ML and LLM models in an operational context.
Power automation, orchestration, and closed-loop decisioning.
Implements federated, fine-grained access control and compliance frameworks across all operations.
Ensures zero-downtime upgrades, continuous deployment, and resilient operation across on-premise, cloud, or edge environments.
The architecture's strength lies in its semantic integration—linking AI insights directly to operational action through a shared ontology and modular service mesh.
The Ontology Layer is the semantic core of the AI Mesh. It bridges the gap between raw data and meaningful business context, enabling AI, analytics, and workflows to operate over a shared, dynamically updated model of the enterprise.
The ontology acts as a live digital twin, mapping real-world entities—such as assets, customers, orders, or equipment—into ontology objects connected through relationships.
Each object carries contextual metadata (attributes, lineage, status, and event history) that continuously updates as new data streams in. This enables real-time operational awareness and situational intelligence.
Unlike static schemas, the ontology fuses structured and unstructured data from disparate systems—ERP, IoT, databases, documents—into coherent, business-aligned entities.
Example: Sensor data from a machine and its maintenance schedule from SAP merge under a single ontology object representing that machine, allowing AI models to "understand" and act upon it in business terms.
The ontology encodes business rules, dependencies, and workflows. This allows both human and AI agents to reference or modify operational states directly through the ontology.
This modeling transforms the ontology from a static semantic layer into a living operational knowledge graph, where AI-driven decisions automatically align with enterprise logic.
AI models (including LLMs and predictive models) are trained and executed within the context of the ontology, ensuring that outputs are relevant, interpretable, and actionable.
Instead of isolated data predictions, models return insights tied to ontology-defined objects—e.g., "flag delayed shipment X" rather than "flag row ID 3245."
Because the ontology updates continuously from live data streams, operational applications can both read and write back to it.
This supports closed-loop systems where AI insights automatically trigger workflow actions, human approvals, or downstream automations—all while maintaining traceability and context.
The ontology supports modular design: users and developers can define, reuse, and extend objects and relationships to match evolving missions.
This composability accelerates application development, enabling new AI workflows or domain models to be assembled quickly without re-engineering foundational data structures.
Each ontology object is governed by fine-grained access controls integrated with Foundry's federated security model. This ensures that teams can collaborate securely across departments and partners while maintaining compliance and auditability down to the object-property level.