Data governance in Palantir Foundry
At Galde we implement data governance inside Palantir Foundry, not in a separate document: owners, permissions, classification of sensitive information, lineage and control of AI workflows, from the first use case.
Why governance belongs inside Foundry
Foundry has strong controls —access markings, lineage across pipelines, data quality checks— but they only help if they are designed from the first use case. Left for later, every new application inherits improvised permissions and AI works on data nobody has validated.
What we do
Owners and RACI matrix
Who is accountable for each piece of data and each Ontology object, and who decides on changes.
Permissions and classification
Access markings, roles and classification of sensitive information, modelled before the first dataset lands.
Data lineage and quality
Traceability from source to application, and quality checks in the pipelines.
Control of AI workflows
Which data each AIP agent can use, with which permissions and with human oversight where it is needed.
GDPR compliance
Purpose, minimisation and traceability documented in the platform itself.
Start by measuring: Galde Governance
Our method for moving from diagnosis to governance that is actually in place. The free Health Check scores your maturity across 8 dimensions in 15 minutes; the Governance Blueprint identifies gaps, regulatory risk and priorities, and the Golden Path sets out what to implement first in Foundry, over 30, 90 and 180 days.
With MVP60™
The first use case reaches production in 60 days, and every technical decision is documented so your team can maintain it.
Frequently asked questions
Why design data governance from the first use case?
Because in Foundry permissions, lineage and quality are inherited: what is designed well in the first case is the foundation for the next ones, and what is improvised gets carried along.
Does it help if we already have Palantir running?
Yes. We review the permissions, dataset organisation, lineage and Ontology of the current implementation, and propose how to put them in order.
How does it relate to GDPR and AI?
Governance defines which data each application or agent may use and for what purpose, and leaves the traceability in the platform so you can prove it.
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