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Date published: 2026-10-06
Anthropic’s Claude Opus 5.5 and Claude Sonnet 5 are now available in AIP for UK-georestricted enrollments with Claude via AWS Bedrock enabled.
To use these models:
We want to hear about your experiences using language models in the Palantir platform and welcome your feedback. Share your thoughts with Palantir Support channels or on our Developer Community ↗ using the language-model-service tag ↗.
Date published: 2026-10-06
Support for ontology interfaces in Workshop is now generally available and enabled by default across enrollments. This enables you to build Workshop applications against interface properties and links shared by multiple object types without configuring the same workflow separately for every implementing object type.
In Workshop, you can now:

An object table widget configured with an interface object set composed of two object types implementing a manufacturing asset interface.
For example, you can define an Alert interface implemented by Maintenance Alert, Inspection Alert, and Safety Alert object types. Then, you can create one interface-based object set variable, filter it by shared properties, such as Event Date or Status, and display the results with a single widget configuration. When another object type implements the interface, that object type is included in the same interface-based workflow without the need to change the object set variable or reconfigure the module. Previously, you needed to create a unioned object set with more complex conditional application logic to achieve a similar result.

An interface-based object set composed of two object types filtered to include acknowledged asset alerts.
Currently, not all widgets support ontology interfaces. When you pass an interface-based object set to an unsupported widget, Workshop displays an Interfaces not yet supported notification. The widget treats the input as an object type–based object set with property selection options derived from the implementing object types rather than the interface.

A widget configuration displays an Interfaces not yet supported notification and explains how the widget treats the object set.
Learn more about how to use ontology interfaces in Workshop.
Ontology interface support will be broadened to include other major widgets, including the Map, Pivot Table, and Gantt Chart widgets. To help prioritize support for additional widgets, share your thoughts with Palantir Support channels or on our Developer Community ↗ forum using the workshop tag ↗.
Date published: 2026-10-01
AIP Analyst now gives teams more ways to configure shared defaults and workflow guidance. New model categories simplify model selection, while compact view keeps conversations focused on your questions and the agent’s responses.
Administrators can now set default search scopes and a default model category through the AIP Analyst extension in Control Panel. Users starting a new analysis directly in AIP Analyst inherit defaults from their primary organization for settings they have not configured. They can override these defaults in Settings.
Organizations can also require watermarks on PDF exports.

Users receive their primary organization's settings by default, user defaults can be updated in the settings dialog.
Administrators can now assign AIP skills to user groups from Control Panel. Assigned skills automatically appear in members’ Skills settings, making shared guidance available without each user having to add it individually.
Use group skills to share instructions for common workflows, recommended object types and relationships, or guidance for interpreting results. Administrators choose which skills are enabled by default, and users can toggle inherited skills on or off. AIP Analyst loads an enabled skill’s full instructions when relevant to a question.

Configure skills for a group in the Control Panel app.
AIP Analyst now offers three model categories: Fast, Balanced, and Smart. The models behind these categories are updated as newer, more capable models become available.
Choose your preferred default category in Settings > Models, or switch categories from the chat. You can also configure a specific model for each category. Custom overrides do not receive automatic model updates, so you may miss newer models until you restore the category’s default.
Workshop builders can also configure the models used for each category and choose the default category for their widget.

Select a Fast, Balanced, or Smart model depending on the task.
Enable Compact view in Settings > General to collapse tool activity under concise status labels that update as AIP Analyst works. Your questions and the agent’s text responses remain visible. Expand the activity summaries whenever you want to inspect tool results.
You can also enable Hide thinking details to hide the model’s thinking content. Workshop builders can configure both options through Compact tool views and Hide thinking details.

Compact mode minimizes tool views, keeping focus on the summaries.
We want to hear about your experiences using AIP Analyst in the Palantir platform and welcome your feedback. Share your thoughts with Palantir Support channels or on our Developer Community ↗ using the aip-analyst tag ↗.
Date published: 2026-10-01
The following models are now available in AIP through Fireworks for US georestricted commercial enrollments:
Existing availability for non-georestricted (GLOBAL) commercial enrollments continues.
To use these models:
We want to hear about your experiences using language models in the Palantir platform and welcome your feedback. Share your thoughts with Palantir Support channels or on our Developer Community ↗ using the language-model-service tag ↗.
Date published: 2026-10-01
We're excited to announce support for reading and writing Foundry Iceberg tables directly in Pipeline Builder's Faster pipelines. You can use Iceberg tables as inputs, perform custom logic and transforms, and output Iceberg tables. This new capability provides greater flexibility and performance when building data transformation pipelines.

A Faster pipeline with Iceberg inputs and an Iceberg output
Use Iceberg alongside existing Foundry datasets in Faster Pipelines. You can read datasets and write Iceberg outputs, or use Iceberg tables as inputs to downstream transformations.
Iceberg support in Pipeline Builder can help improve performance and provide additional flexibility when optimizing existing workflows or building new ones.
We want to hear about your experiences using Iceberg in the Palantir platform and welcome your feedback. Share your thoughts with Palantir Support channels or on our Developer Community ↗ using the iceberg ↗ tag.