Palantir AIP powers real-time, AI-driven decision-making in the most critical commercial and government contexts around the world. From public health ↗ to battery production ↗, organizations depend on Palantir to safely, securely, and effectively leverage AI in their enterprises — and drive operational results ↗.
In short, Palantir AIP connects generative AI to operations. Together with Foundry – Palantir’s data operations platform – and Apollo – Palantir’s mission control for autonomous software deployment, AIP is part of an AI Mesh that can deliver the full gamut of AI-driven products, from LLM-powered web applications to mobile applications using vision-language models to edge applications that embed localized AI. We call this entire set of capabilities, functionality, and tooling the Palantir platform.
While many factors contribute to achieving and scaling operational impact with the Palantir platform — including AIP Bootcamps ↗, where customers are hands-on-keyboard and achieving outcomes with AI in a matter of hours — the key differentiator is a software architecture which revolves around the Palantir Ontology.
permalinkThe Ontology
The Ontology is designed to represent the decisions in an enterprise, not simply the data. Every organization in the world is faced with the challenge of how to execute the best possible decisions, often in real-time, while contending with internal and external conditions that are constantly in flux.
The complexity of these decision processes is reflected in the Ontology, which facilitates deep, two-way interoperability with existing enterprise systems. The Ontology automatically integrates the relevant data, logic and action components into a modern, AI-accessible computing environment. This unlocks the rapid development of operational applications with AI teaming, in addition to conventional business intelligence and analytical workflows.
Decision components
Every decision can be broken down into data, logic, and actions.
- Data: What are the relevant facts or truth about the world and our operations that form the context for this decision?
- Logic: What organizational or business rules act as guardrails for this decision? What are the probabilities of certain outcomes under different assumptions? What have we done in previous, similar situations and what have the outcomes been? What are the inputs from our forecasting and optimization models?
- Actions: What are the “kinetics” or effects of this decision – that is, how does the decision manifest in the world? How do we reduce or collapse the steps between taking a decision in AIP and affecting an outcome in a production setting?
In the Palantir platform, all of these components are designed to facilitate AI teaming patterns to unlock the full potential of your operators, analysts, and subject matter experts.
Suggested reading
To learn more about how these decision components interact to guide workflow development, refer to the documentation on distilling functional requirements as part of the use case lifecycle, or find examples of industry-specific end-to-end workflows in the AIP Now showcase ↗.
Data
The Ontology integrates data as objects and links in order to make the real-world complexity of operations understandable for both humans and AI. This unlocks the ability to build Human + AI teaming workflows.
The Ontology natively supports a wide range of data types as well as a number of extended primitives, such as semantic search for unlocking unstructured data, media references for working with images and video, and value types for embedding additional constraints and context into data. These are the data building blocks for AI workflow development, described further in the Logic and Actions sections below.
This data model powers out-of-the-box applications for exploring structured, unstructured, geospatial, temporal, simulated, and other data modalities. These baseline tools are enriched with the context-aware AIP Assist to dramatically shorten the time-to-value when exploring and analyzing data in the platform.
In addition to application building and analytics, modeling data in the Ontology automatically creates a robust API gateway and Ontology Software Developer Kit (OSDK) to serve as an “operational bus” for connectivity throughout the enterprise.
Posted from:https://www.palantir.com/docs/foundry/platform-overview/overview/