AIP

Palantir AIP (Artificial Intelligence Platform) is a commercial and government-grade platform that embeds large language models and other AI directly into operational workflows. It is designed for organizations that need to move beyond chat-based AI experiments and instead deploy AI agents that can propose, execute, and document real-world actions within existing enterprise systems. AIP is built on top of Palantir Foundry and its core Ontology, which provides a structured, governed representation of an organization's data and operations. The platform is used across at least 12 industries, including aerospace, automotive, energy, financial services, government, healthcare, logistics, manufacturing, media, retail, and telecommunications. AIP targets large enterprises and government agencies that require compliance, security, and auditability — not small teams or casual AI users. A free tier on build.palantir.com is available in perpetuity with no time limit, removing the previous 30-day trial and $500 credit restriction.

AIP's key capability is the AI Workflow Builder, an interface for constructing AI apps, actions, and agents using drag-and-drop logic. The platform uses the Ontology SDK to anchor AI development in the operational truth of the enterprise, meaning AI agents can only act on data and objects that have been modeled and governed. AIP compute usage is metered in tokens (for LLM calls) and compute-seconds (for custom model inference and training). The platform supports both prebuilt AI products (starter packs and example applications via AIP Now) and custom AI products built from scratch. End-to-end evaluation tooling allows teams to test and iteratively improve AI-driven workflows before promoting them to production. Human operators remain in the loop for approving AI-proposed actions, with full visibility into execution rules and history.

In the AI orchestration market, AIP competes with platforms like Elementum (which markets itself as a Palantir alternative for supply chain AI) and MightyBot (a no-code AI automation platform). Unlike these alternatives, AIP is deeply tied to Palantir's Foundry ecosystem and its proprietary Ontology architecture. This gives AIP an advantage in complex data environments where governance and lineage are critical, but it also creates a lock-in effect: organizations must adopt Foundry and the Ontology model to use AIP effectively. AIP's closest conceptual competitor is probably a combination of data science workbenches (like Dataiku or H2O) and automation platforms (like UiPath), but AIP is unique in its focus on AI agents that operate directly on a governed data model.

The honest trade-offs are significant. AIP demands skilled personnel — data engineers, ontology modelers, and AI specialists — to configure and maintain. The upfront investment in Foundry licensing, infrastructure, and integration is substantial, and pricing remains opaque, quoted per organization based on deployment scale, user count, data volume, and integration complexity. The proprietary Ontology architecture creates a permanent specialist dependency: once an organization builds its operational model on the Ontology, switching costs are extremely high. For organizations that do not already use Palantir Foundry, the total cost of ownership can be prohibitive. AIP is not a tool for quick AI experiments; it is a platform for productionizing AI in environments where failure is not an option.

Usage-based pricing tailored per organization; free perpetual tier available on build.palantir.com. Costs determined by deployment scale, number of users, data processing requirements, and integration complexity. No published tiered pricing.