Palantir AIP

What it does

Palantir AIP connects LLM-powered agents and workflows to an organization's data. Data from varied sources and formats is mapped into an Ontology, and AIP turns it into AI-driven workflows, agents, functions, and applications. Builder tools including AIP Logic, AIP Chatbot Studio (formerly AIP Agent Studio), and AIP Evals are used to develop these on top of the Ontology and a developer toolchain.

Teams use AIP to automate operational processes, with developers and frontline users working in the same environment. Generative AI runs inside sandboxed, autoscaling applications that inherit existing security, audit, and resource management controls. Access controls, encryption, auditing, and governance tools with historical lineage are built in. Model management supports version control, and audit trails, explanations, and evaluations are available for model decisions.

AIP is aimed at enterprise organizations and developers, with frontline users interacting with the resulting apps. It is part of a Foundry enrollment and is not documented as a standalone product. Feature availability can change and may differ between customers, so confirm your entitlements with Palantir. Request a quote for pricing and enrollment terms.

What it can do

• Connects LLM-powered agents and workflows to data from varied sources and formats within a Foundry enrollment
• Builds production workflows, agents, and functions with AIP Logic, AIP Chatbot Studio, and AIP Evals on top of the Ontology
• Runs sandboxed, autoscaling applications that embed generative AI within existing security and audit frameworks
• Provides access controls, encryption, auditing, and built-in governance tools with historical lineage
• Supports model management with version control and collaboration across the model lifecycle
• Generates audit trails, explanations, and evaluations of model decisions

Example workflows

Build an AI assistant over PDF documents

Illustrative example based on the documented Speedrun course. Input: PDF documents. Steps: extract information from the PDFs, incorporate it into the Ontology, configure an AIP Chatbot on the resulting knowledge graph, then build an interactive application to use the chatbot. Output: an interactive AI assistant application grounded in the extracted data.

Automate an operational process with an AIP workflow

Illustrative example of the documented tools. Input: organizational data connected through Foundry. Steps: model the data in the Ontology, build the workflow or agent with AIP Logic or AIP Chatbot Studio, and evaluate it with AIP Evals. Output: an AI-driven workflow or agent deployed within existing governance controls.

Before you choose

• Feature availability is subject to change and may differ between customers, so confirm entitlements before planning.
• AIP depends on a Foundry enrollment; it is not documented as a standalone product.
• Palantir's documentation on LLM handling of prompts refers to third-party-hosted LLMs; review its security FAQs before sensitive use.

Listed under

• Operations
• Workflow automation
• AI agents
• Data platform
• Decision making
• Developers
• Enterprise AI
• Financial services

Get started

Use requires a Foundry enrollment; hands-on starting course is available on the learning portal.

1. Obtain a Foundry enrollment through Palantir, since AIP operates on Foundry data.
2. Work through the 'Get started with AIP' page and the conceptual courses on learn.palantir.com.
3. Complete the hands-on 'Speedrun: Your First AIP Workflow' course to build a first AI assistant.

Confirm AIP access, Foundry enrollment, deployment and usage terms with Palantir. A self-service subscription amount is not quoted here.

We couldn’t find published prices for Palantir AIP. See their pricing page ↗

Sources for this overview

Product pages, documentation, and pricing checked 28 Oct 2026. Each source supports part of the overview; availability and prices can change.

• Overview • AIP • Palantir ↗www.palantir.com
• Get started with AIP • Palantir ↗www.palantir.com

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Last checked 28 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.