How Palantir Foundry Extends Your Data Platforms

Palantir Foundry is sometimes incorrectly thought of as a data platform solution. In a way, this confusion is understandable. For organizations that are earlier in the digital journey, Foundry can serve this purpose — providing key functionality such as data integration, management, governance, and search and analysis.

Foundry’s focus, however, extends beyond those capabilities toward its ultimate aim: enhancing the operational decisions that constitute an enterprise. While data platforms do important work in centralizing and managing data in a single place, Foundry is designed to connect analytics to operations — continuously and dynamically in a complex world. As a result, it is best thought of as an operating system that coordinates the interplay of data, models, and decisions in an enterprise.

This orientation requires a different architecture. Below, we discuss how Foundry’s capabilities can dramatically extend the traditional value proposition of a data platform, building operational connectivity.

Data platforms — like Snowflake, Google BigQuery, AWS Redshift, IBM Db2, Azure Synapse, Teradata, etc. — are ideal for consolidating large volumes of data from multiple sources, providing structure, and deriving insights.

In a fast-changing world subject to significant macro shocks, however, many organizations see the need to move beyond insight delivery: They want to give decision makers the technological levers to take action. In practice, this means enabling decisions across functions to be simulated, implemented in underlying systems, and cycled back into a common data foundation for feedback-driven improvement.

Given the complexity of today’s operating environments, software needs to coordinate decisions in ways that are both dynamic (i.e., agile in response to changing external conditions) and scalable (i.e., optimized across teams, regions, and even business units). This capacity requires capabilities that reside outside of traditional data platforms — such as model integration, a dynamic semantic layer, rapid application building, and decision simulation and write-back.

Palantir Foundry Fuels Decisions

Foundry is designed for deep operational connectivity — empowering organizations to close the loop between their data, analytics, and operational decisions.?To fuel operational connectivity, Foundry extends your existing data platforms with capability stacks that include model integration, dynamic ontologies, modular workflows, and decision orchestration.

Palantir Foundry can extend your organization’s data platform into the operational sphere in four key ways:

Model / AI Integration & Creation

Model development and integration in Foundry is a first-class set of capabilities, spanning the entire MLOps lifecycle. It integrates machine learning, artificial intelligence, statistical, and mathematical models with other components of the Foundry ecosystem, allowing models to be chained together and operationalized across diverse workflows. This layer’s core capabilities include the ability to develop, discover, manage, and deploy models.

• Automated, software-defined integrations?rapidly connect data and models outside of Foundry. Connections can be made via native platform integrations (e.g., AWS Sagemaker, Azure ML, DataRobot, Databricks) or by importing your model artifact directly into Foundry as code, libraries, or trained models. Support for all major open-source frameworks such as PyTorch, TensorFlow, and SKLearn — as well as interoperability standards (ONNX) — streamlines integrations.
• Foundry Code Workbooks?enable native, secure data access for model builders using dataset and ontology paradigms as they perform end-to-end model development.
• Foundry Model Management?offers ongoing evaluation and monitoring of deployed and candidate models, as well as multi-stakeholder approval and release processes for deploying improvements into operations. Foundry features full versioning, branching, reproducibility, security, and lineage for your integrated data and models.
• Model Objectives, a “mission control” for models used in Foundry workflows,?ensure that your business logic is tied to specific business KPIs and deployed for a consistent purpose across use cases.

Dynamic Ontology & Semantic Layer

Foundry integrates all relevant data, logic, and models into a digital representation of your organization, called an ontology. The ontology goes beyond business objects and relationships, encoding advanced data semantics (spatial, relational, temporal), “kinetics” (reflecting complex chains of write-operations and system integrations), and granular permissions — all exposed via both UIs and secure APIs. An ontology is quick to bootstrap, and typically grows over time with new workflows, capturing additional data sources, objects, relationships, interactions, and processes.

• A digital representation of your business?reflects both the key semantics of your world (objects and relations) as well as the key kinetics of your world (functions, actions, and models).
• Decision and data capture?ensures that workflows can scale without fracturing the core data foundation, which will continue to serve as a trustworthy source of truth for the enterprise.
• Native “scenario-aware” functionality?allows for what-if analysis and running compound simulations.

Modular Workflows & Applications

Foundry includes a rich set of building blocks for quickly assembling workflows and read-write operational applications (versus simple read-only dashboards). These include the semantic and kinetic primitives discussed above, allowing your teams to configure high-quality interactive workflows for frontline users in hours.

• No/low-code application builders?leverage the ontology and provide a highly-flexible framework for users to interact with your organization’s data asset, while managing the underlying storage, compute, ontological data, model bindings, and security paradigm.
• WYSIWYG, widget-driven builders?offer interaction with both ontological data, as well as tabular/SQL-shaped data.
• “Low floor & high ceiling” flexibility?allows you to build anything from spartan applications for a small group, to mission-critical applications at the core of operations centers.
• Open APIs?ensure the platform accommodates an evolving technology landscape.

Decision Orchestration

This layer provides the technical bridge between your organization’s analytics and its operational workflows. As operators, business processes, and systems make decisions and take action, this layer writes the results back into the ontology, providing feedback loops for high-velocity organizational learning.

• Extensible, bidirectional connectors?allow Foundry to record and write back all decisions to your organization’s ontology as well as to its operational/transactional systems (e.g., ERP, CRM, MES, Asset Config, Edge). Foundry maintains a complete log of both decisions and states to ensure auditability and full transparency.
• Simulations?give users access to powerful “what-if” analysis and decision exploration, enabling them to simulate possible actions and evaluate how they would affect the business. Simulations can be tactical or long-lived, refreshing along with data and models.
• Full lineage?is maintained from data to decision, allowing you to ask, “What was the state of the world?” when a particular piece of data or metadata was written externally. Decisions are always non-destructive since Foundry brings in underlying data through system integrations and versions all changes.

These capabilities animate a unique form of operational connectivity that drives success across industries — from the?World Food Programme delivering life-saving assistance , to?pricing optimization at a large beverage company , to?inventory optimization at a global manufacturer , and?many more .

Looking to close the loop between analytics and operations??Get in touch ?with a member of our Foundry product team.