Skip to content
storyUnited StatesConsumer DiscretionaryCapability

Story

Palantir@Genuine Parts

Palantir at Genuine Parts: Feature Pipelines

Genuine Parts, a consumer discretionary organization in the United States, uses Ontology from Palantir to support applied machine learning for data scientists and ML engineers.

Value results

CategoryValue result
CapabilityData scientists and ML engineers work from the same Ontology record for feature pipelines
CapabilityFeature pipelines can be reviewed without waiting on a personal export
CapabilityNamed workflow replaces ad hoc routing for feature pipelines

Story

Genuine Parts grew feature pipelines faster than the local tools around it. From the United States, consumer discretionary teams still had to serve customers and internal partners who expected a straight answer. Data scientists and ML engineers were the ones stitching the picture together by hand.

Rolling out Ontology put applied machine learning on Palantir. Palantir builds data operating systems and AI platforms used by governments and enterprises to integrate operational data and decision workflows. Genuine Parts keeps the product in the path where work already happens, so data scientists and ML engineers do not context-switch into a graveyard system used only for audits.

The visible result is steadier applied machine learning. Feature pipelines is easier to inspect, and adjacent groups can join data scientists and ML engineers without a guided tour of someone's desktop.

Relationship map

Genuine Parts uses Palantir, Qualtrics, Grafana Labs, Informatica, Unity. Shared with Abnormal Security, Accenture, Adyen, Aker Solutions, AMETEK. Industry: Consumer Discretionary. Value: Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

100%

Similar stories

Search Valuerepo

Search stories, solutions, customers, and more.

Type to search stories, solutions, and companies

↑↓Navigate↵OpenEscClose

View all