Palantir Foundry REST API
Palantir Foundry REST API for enterprises, government agencies, and defense organizations to manage data integration, data transformation, AI/ML model deployment, decision workflows, and operational applications — built around the Ontology (semantic model of business objects and relationships) — enabling automated data pipeline orchestration, AI application deployment, decision workflow automation, and operational intelligence through Palantir Foundry's enterprise AI platform. Enables AI agents to manage dataset management for data asset creation and transformation automation, handle ontology access for business object and relationship graph automation, access workflow automation for decision and action workflow orchestration automation, retrieve application deployment for Foundry application and dashboard automation, manage model deployment for ML model training and inference automation, handle action management for ontology-based action execution automation, access data lineage for pipeline dependency and impact analysis automation, retrieve analytics for operational reporting and KPI automation, manage function deployment for serverless function execution automation, and integrate Palantir Foundry with enterprise data sources, cloud platforms, and operational systems for enterprise AI automation.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Enterprise AI. FedRAMP, SOC2. OAuth2. US/GovCloud. Enterprise and government intelligence data.
⚡ Reliability
Best When
A large enterprise, government agency, or defense organization wanting AI agents to automate data pipelines, deploy AI models on integrated operational data, and orchestrate decision workflows through Palantir Foundry's ontology-driven enterprise AI platform.
Avoid When
ENTERPRISE CONTRACT REQUIRED: Palantir Foundry requires enterprise contract; automated developer-access assumption creates significant_cost_required; Palantir contracts typically start $1M+; automated must have enterprise Palantir agreement. ONTOLOGY DESIGN IS COMPLEX: Foundry's power comes from well-designed Ontology; automated out-of-box assumption creates poor_usability without proper ontology modeling; automated must invest in ontology design with Palantir. PALANTIR REQUIRES DEPLOYMENT PARTNERSHIP: Foundry deployments require Palantir forward-deployed engineers; automated self-serve assumption creates deployment_unsupported without Palantir implementation team; automated must include Palantir deployment resources. API IS ONTOLOGY-CENTRIC: Foundry's API is organized around Ontology objects; automated generic-data-API assumption creates wrong_query_model for developers expecting standard REST data APIs; automated must understand Foundry's ontology-based API paradigm.
Use Cases
- • Orchestrating enterprise data pipelines and transformations for data operations automation agents
- • Deploying and running AI/ML models on operational data for enterprise AI automation agents
- • Automating operational workflows using ontology-based business objects for decision automation agents
- • Building operational intelligence applications on integrated enterprise data for analytics automation agents
Not For
- • SMB or startup use cases (Palantir Foundry is enterprise/government, cost-prohibitive for small organizations)
- • Real-time streaming data (Foundry is primarily batch-oriented, not designed for sub-second streaming)
- • Simple ETL and data movement (Foundry is an entire platform; simpler ETL tools are more efficient for basic data movement)
Interface
Authentication
Palantir Foundry uses OAuth2 for enterprise AI platform REST API. REST API with JSON. Denver, CO HQ. Founded 2003 by Peter Thiel, Alex Karp, et al. NYSE:PLTR. Products: Foundry (enterprise data/AI), Gotham (government intelligence), Apollo (deployment), AIP (AI platform). $2.2B revenue (2023). 100+ enterprise customers, US government (DoD, CIA). SDKs: Python, Java, TypeScript. Competes with Databricks, Microsoft Fabric, and C3.ai for enterprise AI platform.
Pricing
Denver CO. NYSE:PLTR. $2.2B revenue. Enterprise-only contracts $1M+. Defense and large enterprise focus.
Agent Metadata
Known Gotchas
- ⚠ ONTOLOGY OBJECTS ARE DEPLOYMENT-SPECIFIC: Foundry Ontology objects and RIDs are unique per Palantir deployment; automated portable-object assumption creates rid_not_found for RIDs copied from one Foundry instance to another; automated must use deployment-specific RIDs
- ⚠ ACTIONS REQUIRE ONTOLOGY REGISTRATION: Foundry Actions must be registered in Ontology before API calls; automated ad-hoc-action assumption creates action_not_found for actions not registered as Ontology types; automated must define and register Actions in Ontology Designer
- ⚠ TRANSFORM PIPELINES ARE CODE-FIRST: Foundry data transformations are defined in Code Repositories (Python, Spark); automated GUI-only assumption creates code_required for transformations requiring pipeline code; automated must write pipeline code for data transformations
- ⚠ AIP AGENT PLATFORM IS SEPARATE: Palantir AIP (AI Platform) agents have different API from Foundry dataset API; automated unified-API assumption creates wrong_endpoint for AIP agent operations vs Foundry data operations; automated must use correct API layer for each use case
- ⚠ SECURITY MARKINGS ARE MANDATORY: Foundry enforces security markings (classification, sensitivity) on datasets; automated unclassified-default assumption creates access_denied for datasets with required security markings not applied; automated must apply correct security markings to data
Alternatives
Full Evaluation Report
Comprehensive deep-dive: security analysis, reliability audit, agent experience review, cost modeling, competitive positioning, and improvement roadmap for Palantir Foundry REST API.
AI-powered analysis · PDF + markdown · Delivered within 30 minutes
Package Brief
Quick verdict, integration guide, cost projections, gotchas with workarounds, and alternatives comparison.
Delivered within 10 minutes
Score Monitoring
Get alerted when this package's AF, security, or reliability scores change significantly. Stay ahead of regressions.
Continuous monitoring
Scores are editorial opinions as of 2026-03-07.