Announcements
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Announcing Machinery, for building and optimizing your processes in a comprehensive view [GA]
Date published: 2025-05-13
Machinery is an intuitive application for modeling real-world events, such as business workflows, government operations, and healthcare procedures, as processes that can be explored in real-time through custom AI-powered applications tailored to your needs. Machinery will be generally available in the first week of June across all enrollments.
Use Machinery to mine or implement a process and identify unwanted behaviors, and make improvements towards achieving desired outcomes. Additionally, facilitate human input and iteration for manual actions and the reduction of inefficiencies to improve your workflow.
Implement a process from scratch, review, and optimize with Machinery in a comprehensive view.
Common workflows for Machinery include:
- Resolving process inefficiencies with the help of AIP and automation
- Managing an AIP use case end to end by orchestrating several AI agents
- Mining an ongoing process from external event logs to gain visibility into an existing process
- Defining and monitoring performance metrics and expectations to identify process bottlenecks
- Building operational applications to supervise AIP workflows with real-time human intervention
To use Machinery, an enrollment administrator must first enable Machinery in Control Panel.
Optimize your process with automation and AIP
Implementing a process in the Palantir platform involves many individual resources, such as object types, actions, and automations. Machinery now provides a comprehensive view for all these components and lets you inspect and control all relevant details. Its unique state-centric perspective and intuitive graph allow you to draw, define, and understand an ordered flow of actions. Machinery also integrates value types and submission criteria, providing you an additional layer conformance guarantees.
Automation nodes can be built into a Machinery graph.
Machinery will boast an auto-layout feature allowing for visually appealing graphs without need of manual manipulation. Users can also disable this feature and freely move elements, allowing for customized adjustments tailored to individual preferences.
Multiple object type modeling in a single Machinery graph
Create subprocesses, parallel processes, and focus views to benefit from unparalleled flexibility and control over workflows. Subprocesses allow users to create nested processes within your main Machinery process, providing a structured way to manage complex tasks and enabling seamless integration into the larger workflow. This modular approach supports parallel processes, allowing multiple subprocesses to run concurrently, thereby enhancing efficiency and reducing bottlenecks.
You can now build unlimited subprocesses in a given process, allowing for a comprehensive view.
The focus view feature further elevates user experience by allowing users to "zoom in" on specific subprocesses, providing a detailed view that simplifies navigation and management of intricate workflows. With these capabilities, users can achieve a higher level of process automation and visualization, ultimately leading to improved productivity and streamlined operations.
Mining mode
After configuring the log ontology, users can enter mining mode, which presents a distinct graph highlighting both existing states and potential edits in sepia color. Users can exclude certain states from mining, effectively reducing noise and focusing on relevant data. Use the transition frequency slider to filter out less important nodes, ensuring that only the most critical transitions are highlighted while benefiting from the clean auto-layout graph.
Mining an entire process in Machinery mining mode.
Machinery mining mode with a transition filter to filter out nodes that have less than 71.5% objects passing through.
Bootstrap your development by generating a Workshop module
To operationalize your process in the Palantir platform, you can quickly bootstrap a Workshop module ("Machinery Express application") with a single click to initiate your application development. The express application serves as a dynamic playground where you can conduct preliminary analysis and then jump back into Machinery to refine, update, or optimize your processes with actions, automations, and AIP logic functions.
Whether you choose to use Machinery Express as a ready-to-use analysis tool or as a foundation to build your own applications, it facilitates a fluid interaction between process exploration and refinement. Additionally, the Machinery Express application enables you to immediately share this process with your operational users, providing them with the necessary context to effectively engage with the system in real time.
Generate a Machinery Express application to help get you started on application development in Workshop.
If you prefer to build a new application from scratch or add Machinery to an existing Workshop module, you may add a Machinery Process Overview widget in workshop.
For more information on Machinery, review the documentation.
We want to hear from you
As we continue to develop media support in our platform, we want to hear about your experiences and welcome your feedback. Share your thoughts with Palantir Support channels or our Developer Community ↗ and use the machinery ↗ tag.
Python functions can now be run serverless [GA]
Date published: 2025-05-13
You can now run Python functions without any setup or user-managed resources using our high-performance serverless backend. All new Python functions will use the serverless backend unless specifically requested, and deployed Python functions can be switched to the serverless backend with no downtime.
Python functions can be used anywhere in the platform that Typescript functions are used, such as in ontology actions and Workshop. With this functionality, Python functions will execute in a similar manner to Typescript functions, with no user-managed resources.
To get started on a new Python function, review the getting started walkthrough.
If you have existing deployed Python functions, you can migrate them to the serverless backend through Ontology Manager using the dropdown menu.
Existing functions using the deployed backend can be converted to serverless mode in Ontology Manager.
Define module-level color palettes for Workshop applications
Date published: 2025-05-13
Custom colors used within a Workshop application may now be defined and saved on the module level, allowing application builders to set a consistent palette and easily swap out colors used throughout their application. You can access a new Used colors panel from the module’s Settings panel which stores Saved colors defined by the builder and Unsaved colors used in the module.
An example Workshop application, displaying saved and unsaved colors in the Settings panel.
- Saved colors are defined by the application builder on the module level. Builders may add colors to the Saved colors section that will allow these colors to be selectable when configuring custom colors in layouts and widgets. Builders may rename the saved colors they have defined, set separate colors to be used in light and dark modes for modules, and view color usage in layouts and widgets within the module. Saved colors may be easily edited by the builder and propagated to all layouts and widgets using the saved colors feature, allowing builders to quickly and easily update colors within their module.
- Unsaved colors represent custom colors not set in the Saved colors section used in layouts and widgets throughout the module. Builders may select to copy the hex code of unsaved colors to be easily used elsewhere and may also view the usage of these colors in layouts and widgets within the module.
To learn more about Workshop's used colors feature, review the product documentation.
GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano are now available in AIP through Direct OpenAI API
Date published: 2025-05-13
OpenAI’s GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano are now available for general use in AIP through Direct OpenAI API. GPT-4.1 is OpenAI’s flagship model for complex tasks and an improvement over GPT-4o for similar use cases, while the mini and nano models provide lower latency and costs. Comparisons between OpenAI’s models can be found in GPT-4.1’s release notes ↗. As with all new models, use-case specific evaluations are the best way to benchmark performance on your task.
GPT-4.1 models are available for enrollments that have accepted our AIP contract addendum and enabled Direct OpenAI usage in Control Panel. GPT-4.1 models are not currently available through Azure OpenAI or for geo-restricted enrollments yet. We will share an update when GPT-4.1 models through Azure are available in AIP. If your enrollment does not currently include these features, ask an enrollment administrator to review the AIP enablement settings and documentation.
GPT-4.1 models are available to use in all AIP features such as AIP Logic, Pipeline Builder, functions, transforms, and more.
GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano recommended in Model Catalog.
Text nodes now available in Pipeline Builder and Workflow Builder
Date published: 2025-05-13
Text nodes is a new feature designed to help annotate and document your graphs in Pipeline Builder and Workflow Builder [Beta]. Text nodes allow you to add descriptions and explanations directly in your workspace, making it easier to highlight important information and provide context where needed.
The Add new text node option, available in both Pipeline Builder and Workflow Builder.
Key features
- Markdown support: Text nodes use Markdown, enabling you to format your text with ease.
- Customizable colors: Just like regular nodes, you can color text nodes to suit your graph's theme or emphasize sections.
- Independent layout: Text nodes are not affected by layout changes and remain independent of other nodes, providing flexibility in documentation placement.
Examples of text nodes in a Pipeline Builder graph.
Get started with text nodes
To add a new text node, select the Add new text node option located in the upper left of your workspace in either Pipeline Builder or Workflow Builder.
Adding a new text node in Workflow Builder.
After adding a text node, you can edit text content by double-clicking the added node and entering Markdown content. You can adjust the size of the text node using the three lines in the bottom right corner. If your text exceeds the node's length, it will automatically become scrollable.
Sample Markdown content in a text node, with three lines in the bottom right corner used to resize the node.
After adding text content, you can color-code your text nodes by right-clicking a node and selecting Color nodes from the context menu. Choose from existing colors to match relevant nodes, or create new colors to highlight important information.
The option to add a new color in a Pipeline Builder text node.
Embed text nodes in your pipelines and workflows to give users a comprehensive understanding of graph sections and the ability to update relevant information as workflows evolve from a single, cohesive interface.
Share your thoughts
We want to hear what you think about our updates to Pipeline Builder and Workflow Builder. Send your feedback to Palantir Support teams, or share it in our Developer Community ↗ using the pipeline-builder ↗ and workflow-builder ↗ tags.
Learn more about text nodes in Pipeline Builder and Workflow Builder.
Compare output statistics for proposals in Pipeline Builder
Date published: 2025-05-13
Pipeline Builder now lets you view and compare output statistics on any node within a proposal to the corresponding node from the original branch.
View and compare output statistics on any node for any column with the Comparison view in Pipeline Builder.
Benefit from the new Statistics panel and access a variety of metrics, including the following:
- General metrics: Number of null and unique values.
- String metrics: Minimum and maximum lengths, and count of strings needing trimming.
- Numeric metrics: Minimum, maximum, median, standard deviation, and count of negative and positive values.
You can also easily identify differences between the statistics of your branch and the main branch with color-coded metrics displayed to the right.
To access, start from the Proposals (or History) tab, and select Changes for the proposal.
Use the Changes option.
Double-click into the transform for which you want to see statistics, then select Statistics at the top right or use the tab on the bottom panel to access the statistics view.
Use the Statistics view to explore and compare statistics for selected columns.
Learn more about these proposal statistics in the documentation.
Indefinite conversation retention in AIP Agent Studio and AIP Threads
Date published: 2025-05-06
Indefinite conversation retention is now supported in AIP Agent Studio and AIP Threads, allowing users to access conversation history and context past the previous limit of 24 hours. This feature is optional in AIP Agent Studio, and is on by default for most configurations in AIP Threads.
AIP Agent Studio
To opt in to indefinite conversation retention for an AIP Agent, select the Indefinite retention setting in the Conversation settings tab.
AIP Agent Studio conversation retention settings.
This configuration applies to a specific AIP Agent and version, and will apply to future versions unless disabled. Setting this configuration on one agent will not affect other agents. Previous versions of an agent that do not have this option enabled will not have indefinite conversation retention. This feature should be configured individually for all agents, and the changes must be saved for indefinite retention to take effect.
To differentiate conversations with 24-hour retention vs. indefinite retention, a banner will be displayed in AIP Agent Studio and Workshop for agents with finite retention.
An AIP Agent configured with 24-hour retention In AIP Agent Studio.
Note that restricted view-backed object types are not supported with indefinite conversation retention. If you add a restricted view dependency to your agent, you will be unable to select the Indefinite retention option.
AIP Threads
In model mode, conversations will automatically opt into indefinite retention. In AIP Agent mode, conversations will assume the retention configuration of the AIP Agent.
AIP Threads conversations marked with indefinite and 24-hour retention.
Share your feedback
As we continue to develop AIP Agent Studio and AIP Threads, we want to hear about your experiences, and welcome your feedback. Share your thoughts with Palantir Support channels or our Developer Community ↗ using the aip-agent-studio ↗ and aip-threads ↗ tags.
For more information, review the AIP Agent Studio and AIP Threads documentation.
Introducing the new Workshop Map widget
Date published: 2025-05-06
Starting the week of May 5, the Workshop Map Application Template widget will become the Map widget, while the existing Map widget will be renamed to the Map [Legacy] widget. Going forward, the new Map widget is the recommended widget for geospatial workflows, providing better performance, new features, and more flexibility for large scale data.
Why did we make this change?
This change aims to clarify the recommended widget for geospatial workflows. We recommend that users consolidate map usage in Workshop to a single widget to minimize confusion for module builders, focus development efforts, and improve support timelines. There is considerable overlap between the two widgets, but the new Map widget focuses on large scale data and usability, so it is not intended to have exact feature parity with the Map [Legacy] widget. The Map [Legacy] widget will still be available, but is only recommended for mobile workflows and environments without WebGL. Module builders can opt to manually migrate to the new Map widget, but no action is required.
Advantages of the new Map widget
The new Map widget has the following advantages over the Map [Legacy] widget:
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Support for large scale object sets in the order of millions of objects, compared to the 10 thousand object limit of the Map [Legacy] widget.
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Tile-based rendering that enhances performance when handling complex geometries.
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Dynamic layer visibility based on zoom levels.
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A simple, more intuitive layer style configuration.
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Removes the need to create external resources; the new Map widget can be fully configured in the Workshop widget editor.
A sample map where layer styles are controlled by the widget configuration.
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Facilitates moving tracks and layer styling backed by time series properties, along with advanced timeline interactions.
A sample map that explores the prevalence and magnitude of earthquakes using timeline and time-based layer styles.
Share your feedback
For more information on these changes, review the new Map widget documentation, how it differs from the Map [Legacy] widget, and Map application capabilities.
As we continue to develop Workshop and the Map widget, we want to hear about your experiences and welcome your feedback. Share your thoughts with Palantir Support channels or our Developer Community ↗ using the map tag ↗.