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Palantir
Data analytics platform company building AI-powered software for government and enterprise clients.
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Securing Software at the Speed of AI
Palantir describes how its Product Security Team built an agentic software security strategy around multi-agent review, vulnerability hunting, triage, and runtime validation. The approach treats models as replaceable components within a governed harness that controls tools and data access, preserves evidence, coordinates specialized stages, independently challenges findings, and deduplicates reports using source-to-sink paths. Foundry supplies organizational context and lineage across code, services, findings, decisions, and remediation, while Apollo provides a controlled path for delivering verified fixes across heterogeneous software environments. The strategy positions remediation, rather than vulnerability identification, as the central bottleneck and extends these capabilities through Security Forge, a model-agnostic platform for customer cyber defense.
AI Sovereignty is Your Alpha: How to Avoid Transferring Your Alpha to a Hosted Model Provider
The document examines how use of third-party AI model services can expose an organization’s “alpha”—institutional knowledge and tradecraft embodied in data sent to and generated from models—to hosted model providers. It identifies risks involving provider reuse, storage, human review, model or service improvement, contractual liability caps, ZDR-ineligible beta services, safety-classifier triggers, and inference routed through prohibited regions. Its recommended approach combines contractual protections with operational controls: define robust Zero Data Retention, limit data use to service delivery, bind both hyperscalers and relevant AI labs, maintain an allow-list, block beta headers, and constrain unilateral term changes. It also calls for observability and contractual incident safeguards, including investigation periods, migration buffers, and regional routing limits, while noting that the document is not legal advice.
Managing Elasticsearch Reindex at Scale: Performance, Reliability, and Observability
Palantir’s document store needs to repair or rebuild Elasticsearch indices when mappings, settings, cluster versions, or index state change, while continuing to serve live search and writes. Its reindex machinery reconstructs schema-aware indices from the strongly consistent database, rather than relying on Elasticsearch’s _reindex API, and is designed to limit manual work and resource consumption across many deployments and schemas. For an online reindex, it creates a physical shadow index with the intended mappings and settings, backfills it from the database, dual-writes current API changes to both indices, and promotes the shadow index after completion; searches remain on the primary during the rebuild. Cross-cluster migrations use a separate machine with cluster-specific metadata, configuration, index and alias evolution, and preservation of old-cluster indices to support rollback.
Enterprise Business Software and the Mixed-Up Chameleon Problem
Traditional ERP practice prioritizes a standardized, stable core, but the post argues that forcing every process into it can erode an organization’s identity and differentiated ways of creating value. It proposes keeping the ERP as the system of record while placing an interoperability layer above it. This layer uses a shared ontology to reconcile concepts across systems and supports workflows, automation, user experiences, agentic AI, and human engineering under shared security and governance. Because these capabilities remain outside the core, organizations can preserve distinctive processes during ERP upgrades and treat migration as a continuous software- and ontology-driven activity rather than a one-time manual exercise. The intended model is structured adaptability: standardized ERP functions retain discipline, auditability, and financial integrity while operational software adapts to the business.
Ready, Set, Build with the NHS Federated Data Platform
The NHS Federated Data Platform (NHS FDP), delivered by NHS England through a consortium led by Palantir, connects operational data held in separate NHS systems while keeping each organisation’s data under local control. Built on Palantir Foundry, its federated tenants use the Canonical Data Model, encryption, purpose-based access, and Privacy Enhancing Technology for national data flows. As of end December 2025, the post reports 110,078 additional theatre procedures, 797,728 patients safely removed from waiting lists, and 297,943 safely discharged patients, alongside around a 15% reduction in observed discharge delays. The inaugural Build with FDP hackathon brought together over 120 NHS developers and analysts, who built 25 working prototypes on a notional Canonical Data Model to address frontline operational challenges. Projects included early-warning, bed-demand prediction, CAMHS demand balancing, and genomic-optimised waitlist tools.
Connecting Agents to Decisions
Palantir’s Ontology is presented as a decision-centric architecture for human-agent operations, intended to represent how enterprises make and execute decisions rather than only storing or analyzing data. It combines data, logic, action, and security in a shared, dynamic representation that can connect operational data, computational processes, workflow execution, and policy controls. The data layer includes structured, streaming, edge, unstructured, imagery, and decision data, with decision lineage recording the data version, application, and decision context; logic binding connects heterogeneous business, modeling, planning, and optimization assets for human and agent workflows. The architecture exposes approved actions to agents with configurable human review and guardrails, while capturing decisions as learning material for improving workflows and agentic memory. It concludes that a real-time ontology can anchor AI in enterprise conditions while controlling where automation is allowed.
Frontend Engineering at Palantir: Engineering Multilingual Collaboration
Palantir describes the frontend work behind adding read-only translation mode to Dossier, a collaborative rich-text editor used in multilingual, restrictive environments where public translation services may be unavailable or disallowed. The design lets users choose source and target languages, view a complete document in translation, copy text, and add comments while routing requests through the in-house Language Model Service. Engineers extracted shared translation components, added a Redux state slice and per-element cache, chunked content by paragraphs and other blocks, and used Intersection Observer, batching, debouncing, and caching to translate visible content incrementally; edits invalidate affected translations and trigger retranslation. To preserve sentence-level quality, inline formatting is stripped before translation, so the current translated view is plain text. The resulting mode is available in every Dossier, translating content lazily as users scroll and updating translated blocks when collaborators edit the document.
Frontend Engineering at Palantir: Polar Scaled Tiles in Zodiac
Zodiac, Palantir’s custom 3D globe library built on Three.js, encountered severe performance degradation near the Arctic because latitude/longitude tiles converge into tiny slivers and create excessive geometry. Standard equal-angular tiling was replaced internally with polar-scaled tiles whose widths expand toward the poles so their surface areas remain closer to equatorial tiles. The design uses spherical surface-area calculations, power-of-two merge spans, and dynamic quadtree expansion; client-side texture compositing handles standard geodetic or Web Mercator sources, while heightmaps are combined and resampled for wider tiles. The change reduced polar geometry, draw calls, and textures by over 90% and made frame time more consistent, though texture loading remains the next bottleneck and native polar tiles would remove stitching overhead.
Frontend Engineering at Palantir: Plotlines in Three.js
Palantir’s frontend engineers are building a 3D implementation of Gaia to visualize Foundry Ontology objects with geospatial properties, including ground locations, satellite positions, and paths through space. The system uses Zodiac, a Three.js library backed by Foundry-based APIs: the backend stores, filters, and computes data, while the frontend receives simplified geometry and style information for rendering. Performance techniques include converting latitude and longitude to Earth-fixed coordinates once, batching similarly styled lines into single draw calls, and using instanced meshes plus batched updates for dense satellite scenes; orbital propagation uses TLEs client-side, while heavier analysis remains server-side. The article also describes frame-synchronized animation callbacks that update material properties without rebuilding geometry, while noting that 3D APIs continue to iterate across usability, platform integration, and performance as new data sources and workflows are added.
Frontend Engineering at Palantir: Building a Backend-less Cross-Application API
Palantir’s Application Frameworks team builds the “backend of the frontend”: frameworks that let applications communicate during workflows spanning multiple interfaces. The work addresses environments with denied, disrupted, intermittent, or limited (DDIL) connectivity, where relying on backend services can introduce unreliable latency. The team generalized the Gaia Controller prototype into Shared State, which lets applications define named data models and exchange updates organized by Media Type, and Commands, which exposes arbitrary logic through command IDs and request objects that return responses. Both frameworks use frontend-only browser APIs for client-side interaction, support workflows such as pairing Gaia with Workshop, and are also being used as tools by AIP agents; the post says adoption is growing across Palantir.
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