05Palantir Foundry
Foundry that reaches operations, not just dashboards.
We design ontologies, build transformation pipelines and ship operational applications on Palantir Foundry — and we make sure your own people can run and extend what we deliver.
01Where it starts
What we usually walk into.
Foundry programmes often stall between data integration and operational use. Pipelines land, dashboards appear, and the decisions the platform was bought to improve still happen in spreadsheets.
We have Foundry, we have data in it, and the business still runs on exports.
The ontology grew organically and now nobody agrees what an "asset" is.
Pipelines break silently and the numbers are quietly wrong.
Our existing Foundry solution was built by people who have left.
We need Foundry connected to systems that predate it by twenty years.
02Approach
How we do the work.
We treat the ontology as the product: a shared operational model of the business, connected to real workflows and writeback, with the pipelines and governance to keep it trustworthy.
- 01
Ontology as the operating model
We model objects, links, actions and permissions against how the business actually works. A good ontology makes later applications small; a poor one makes every application a workaround.
- 02
Pipelines built to be trusted
Transformations are versioned, tested and monitored, with data quality expectations expressed as checks rather than assumptions. Silent drift is the most expensive failure mode in a data platform.
- 03
Applications where the decision is made
We build operational applications and writeback workflows so action happens inside the platform. Analytics that only inform a meeting rarely change an outcome.
- 04
Enablement is part of delivery
We pair with your analysts and engineers throughout and hand over documented, maintainable work. Our aim is that you need us for the next hard problem, not for routine change.
Capabilities and deliverables
Capabilities
- Foundry application development
- Ontology design and refactoring
- Data integration from enterprise and legacy sources
- Transformation pipeline engineering
- Operational workflow and writeback design
- Enterprise analytics modelling
- Platform implementation and rollout
- Modernisation of existing Foundry solutions
- Custom integrations with external systems
- Training and technical enablement
What you receive
- Ontology design: object types, link types, actions and permission model
- Data transformation pipelines with tests and quality checks
- Operational applications and writeback workflows
- Integrations with source systems, both modern and legacy
- Data governance, lineage and access model documentation
- Enablement sessions and written guidance for your team
- Modernisation plan for existing Foundry solutions
Common use cases
- Supply chain and logistics operations
- Asset and maintenance management
- Manufacturing and production planning
- Financial operations and reconciliation
- Regulatory and compliance reporting
- Cross-system operational reporting where source systems disagree
Technologies typically involved
- Palantir Foundry
- Python
- PySpark
- SQL
- TypeScript
- Go
- PostgreSQL
- Kafka
- REST and gRPC integrations
03Engagement
How it runs.
- 01
Assessment
2 weeks
Current platform state, data sources, existing ontology and the operational decisions in scope.
- 02
Ontology & design
3–5 weeks
Target ontology, pipeline architecture, permission model and delivery roadmap.
- 03
Build
Ongoing
Iterative delivery of pipelines, ontology and applications with users involved throughout.
- 04
Enablement
3–6 weeks
Structured training, documentation and a supported transition to your team.
04Security
Security considerations.
These apply to this service specifically. They are engagement conditions, not aspirations, and we will put them in the contract.
- Access modelled through the ontology permission system, not by copying data into side stores
- Data classification and handling rules agreed before integration begins
- Lineage maintained so every derived figure can be traced to its sources
- Least-privilege service accounts for every integration
- Export paths reviewed — an unmanaged export is a data-loss path
05Outcomes
What changes afterwards.
Decisions made inside the platform, against data the business trusts, by people who did not need to become data engineers.
- 01
A single operational model the business agrees on
- 02
Data quality failures surface as alerts instead of as wrong decisions
- 03
Operational decisions move from spreadsheets into governed workflows
- 04
Your team can extend the ontology and pipelines without external help
06Questions
Asked before every engagement.
BYAK is an independent engineering company and is not a Palantir partner, reseller or affiliate. Palantir and Palantir Foundry are trademarks of Palantir Technologies Inc. We build on the platform for clients who already license it — that is the whole relationship, and we would rather state it plainly than let a logo imply something closer.
For build work, yes — licensing is between you and Palantir. We can help earlier than that, assessing whether the platform fits the problem and what an implementation would involve, without a commercial interest in the answer.
Yes, and it is a common request. We start with an assessment of the ontology, pipeline health and application state, then give you a written view of what to keep, refactor or replace before making changes.
We will say so. We build data platforms on other technology as well, so our recommendation is not tied to a single platform choice.
Frequently runs alongside
Ready to scopepalantir foundry?
Bring the problem, the constraints and the deadline. We will tell you what is achievable, what it costs and what we would do first.