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Announcements
REMINDER: Sign up for the Foundry Newsletter to receive a summary of new products, features, and improvements across the platform directly to your inbox. For more information on how to subscribe, see the Foundry Newsletter and Product Feedback channels announcement.
Share your thoughts about these announcements in our Developer Community Forum ↗.
Lower costs for streaming ingestion with Foundry worker
Date published: 2026-11-05
Foundry worker is the recommended method for accessing external systems and replaces the legacy agent worker.
From November 1, 2026, customers can expect to see a reduction of around 97.5% in compute costs for their streaming ingests when running on Foundry worker compared to what it would have been previously. This is intended to facilitate migration from agent worker to Foundry worker.
This builds on our recent pricing announcement, which announced several Foundry worker data operations available without compute cost, by reducing compute costs for streaming ingests as well.
Next step: Migrate your connectors to Foundry worker
If you are currently using agent worker for streaming ingests, we recommend migrating as soon as possible. Learn about the benefits and migration steps in the Foundry worker vs. agent worker guide.
Your feedback matters
We want to hear about your experiences using Foundry Worker in the Palantir platform and welcome your feedback. Share your thoughts with Palantir Support channels or on our Developer Community ↗ using the data-connection tag ↗ .
Search and review audit logs with Audit Explorer
Date published: 2026-11-05
Audit Explorer is a new governance application for searching and reviewing audit.3 audit logs in the platform. Audit logs are an important tool for oversight and accountability of the platform's use. Audit Explorer is specifically designed to facilitate the review of the platform's audit logs, including for security investigations, compliance reviews, and oversight of platform usage.
Audit Explorer's log table, showing recent platform activity and enriched metadata about user and resources. All data is notional.
Audit Explorer is now in the beta phase of development and will be available on selected enrollments at the beginning of November.
Key features
- Search and filter: Filter audit logs by time, user, event type, category, resource, or Ontology resource.
- Charts: See when matching events occurred and which event types are most frequent.
- Logs table: View audit logs in a standardized format, with identifiers for users and resources enriched with context from the platform.
- Log details: See who did what, when, and from where, with readable summaries for events such as Ontology actions and function executions.
- Sessions: Explore user sessions in the platform. If scoped sessions are enabled, view the marking selected for the session as well as the associated checkpoint justifications if configured.
Get started
Audit Explorer reads audit.3 audit logs from an Iceberg table. Organization administrators can create this table of audit logs in either of the following ways:
- In the Audit Explorer application, from the Getting started dialog.
- In Control Panel, by selecting Create Iceberg table on the Audit logs tab.
The Getting started dialog in the Audit Explorer application shows the details for a new Iceberg audit export.
Learn more about Audit Explorer in the documentation.
Audit Explorer is designed for compliance and oversight workflows for authorized users. As a privacy best practice, search audit logs only for a defined oversight or compliance purpose, keeping access limited to those who need it and each search proportionate to the question at hand. Audit Explorer records every search, which keeps reviewers accountable for how they use audit data. Review privacy and civil liberties in practice for guidance on purpose limitation, access governance, and accountability. All uses of Audit Explorer must adhere to Palantir's Acceptable Use Policy ↗.
We want to hear from you
We welcome your feedback and invite you to share your thoughts through Palantir Support or our Developer Community ↗ using the security tag ↗.
DeepSeek V4.1 Flash (1017) support in AIP through Fireworks
Date published: 2026-11-03
AIP adds experimental support for DeepSeek V4.1 Flash (1017) through Fireworks on non-georestricted commercial enrollments, with inference hosted in the United States. Availability depends on the required releases reaching your enrollment and the relevant model settings being enabled.
Model overview
DeepSeek V4.1 Flash (1017) ↗ is an open-weight multimodal model designed for coding, reasoning, and agentic workflows. AIP support includes text and image inputs, tool calling, and a 1-million-token context window.
Getting started
To use this model:
- Confirm that your enrollment administrator has enabled the DeepSeek model family through Fireworks and experimental models.
- Review token costs and pricing.
- See the complete list of models available in AIP.
Bring public web information into your AIP workflows
Date published: 2026-11-03
Web search lets supported OpenAI models in AIP find information from public web sources and return answers with citations. Use web search to research recent developments, consult documentation, and build applications that draw on information beyond a model’s training data.
Web search is supported through Direct OpenAI and Amazon Bedrock on eligible enrollments. Developers can use it through AIP’s OpenAI-compatible Responses API, sending requests from applications and scripts directly or through an OpenAI SDK.
Learn more about using the provider-compatible APIs.
Getting started
Enrollment administrators can enable web search in Control Panel > AIP settings > Advanced AIP Settings. Turn on Enable web search via Bedrock or Enable web search via Direct OpenAI for the provider you want to use. Complete any required Direct OpenAI agreements and save your changes.
Before using web search:
- Confirm that your enrollment administrator has enabled the relevant model family.
- Review token costs and pricing.
- See the complete list of models available in AIP.
Your feedback matters
We want to hear about your experiences using language models in the Palantir platform and welcome your questions and feedback. Share them through Palantir Support channels or on our Developer Community ↗ using the language-model-service tag ↗.
Pipeline builder defaults to faster pipelines, now with LLM support
Date published: 2026-11-03
Faster pipelines are now the default in Pipeline Builder, with new support for Use LLM nodes. You can now build large language model (LLM) workflows in faster pipelines using Palantir-provided models or your own registered models.
Faster pipelines by default
When you create a pipeline from the Pipeline Builder landing page or through AI FDE, faster is now the default selection. Faster pipelines are powered by DataFusion ↗, an open-source query engine written in Rust ↗. Compared with standard Spark pipelines, faster pipelines can reduce execution time and compute resource usage.
Faster pipelines are selected by default when creating a pipeline from the Pipeline Builder landing page.
Use LLM support in faster pipelines
Faster pipelines now support Use LLM nodes and Text to Embeddings nodes with both Palantir-provided models and your own registered models. Bring LLMs into your pipeline to power critical workflows.
The Use LLM board in a faster pipeline with the model selector open.
Tell us what you think
We welcome your feedback. Share your thoughts with Palantir Support channels or our Developer Community ↗ using the pipeline-builder ↗ tag .