Palantir Services

Iseyon builds and operates Palantir deployments for organizations whose decisions cannot wait for a reporting cycle. Palantir Technologies supplies the platform: Foundry for enterprise data integration and operational workflows, Gotham for mission and investigative work, and Apollo for deploying software across many environments, including ones with no network path to the internet. Iseyon supplies the delivery work around it, from the first ontology sketch through to the day your own team runs the platform without us.

Palantir is unusual among data platforms because the unit of work is the ontology rather than the table. Objects, their properties and the links between them are modeled once, then reused by every pipeline, application and workflow downstream. Getting that model right early is most of the engagement, and getting it wrong is expensive to undo. That is why Iseyon starts from a small number of real decisions and works backwards to the data they need, instead of integrating every available source and hoping a use case appears.

Data Integration & Intelligence

Discovery and Ontology Design

Iseyon starts with the decisions the platform has to support, not the systems it has to read. We map the objects your business already reasons about, whether those are assets, cases, shipments, patients or accounts, the properties that matter for those decisions, and the relationships that connect them. That model becomes the contract between source systems and everything built on top, so pipelines and applications stop carrying their own private definition of a customer or a work order.

Source Onboarding and Pipeline Engineering

Iseyon connects sources in priority order rather than all at once. For each one we build ingestion and transformation in Foundry's pipeline tooling, with validation rules, schema expectations and health checks written alongside the transforms rather than bolted on later. Lineage is a property of the build, so when a number is challenged, the path back to the source record is already there to walk.

Operational Applications and Workflows

Analysis nobody acts on does not pay for itself. Iseyon builds the layer that puts objects in front of the people making the call: queues that route work, writeback actions that record a decision against the object, alerting on the conditions your operators actually watch for, and scenario branches for testing a change before committing it. Where the work already happens in another system, the outputs land there.

AI, Security & Deployment

Models in the Loop

Where a decision benefits from a prediction rather than a rule, Iseyon integrates models against ontology objects so features and outputs stay consistent with everything else on the platform. Model versioning, evaluation and rollback are handled as part of the deployment path, not as a research project running beside it.

Governance and Access Control

Iseyon configures access at the object and property level, so a role sees the fields it is entitled to and nothing more, with markings and purpose-based restrictions where the data calls for them. Audit trails, retention rules and approval paths are designed with your security and compliance teams during the build rather than presented to them at the end.

Deployment Across Environments

Palantir installations vary: cloud tenancy, on-premise, disconnected or air-gapped, or some combination. Iseyon plans the promotion path between development, test and production for the environment you actually have, and uses Apollo where continuous deployment across multiple estates is in scope.

Integration With Existing Systems

Iseyon connects Palantir to the systems already running the business: transactional databases, warehouses, historians, ticketing and case management, and internal APIs. Legacy systems are read from and written back to rather than switched off, so modernization happens without a cutover event nobody can schedule.

Handover and Enablement

Iseyon builds so the platform can be run without us. Handover covers the ontology model and the reasoning behind each decision in it, pipeline ownership with on-call runbooks, permission and marking administration, the capacity and cost picture, and enablement for the people who will extend the applications next. The measure of a finished engagement is a client team that no longer needs the call.

Where This Work Lands

Organizations reach for Palantir with a recognizable problem: data spread across systems never designed to answer a question together, and operators who need to act on it now. The shapes of work Iseyon sees most often are fusing multiple sources for mission, case and investigative work in government, joining operational and IT data on the factory floor, monitoring risk across large financial datasets, and asset condition and maintenance planning in energy and utilities. The ontology differs a great deal between them. The delivery pattern differs much less.