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Dataiku@Philip Morris International

Philip Morris International Uses MLOps for Event Streams

Philip Morris International, a consumer staples organization in the United States, uses MLOps from Dataiku to support real-time operations for platform engineers.

In the United States, Philip Morris International relies on Dataiku for real-time operations.

“Consumer Staples work at Philip Morris International spans more than one site, even when headquarters sits in the United States.”
“Platform engineers asked for a shared way to run real-time operations without freezing local judgment.”
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Independent write-up. Figures come from public sources or are illustrative.

Value results

CategoryValue result
CapabilityNamed workflow replaces ad hoc routing for event streams
CapabilityReal-time operations stays visible to adjacent teams through MLOps
CapabilityPlatform engineers work from the same MLOps record for event streams

Story

Consumer Staples work at Philip Morris International spans more than one site, even when headquarters sits in the United States. Event streams was splitting across regional habits. Platform engineers asked for a shared way to run real-time operations without freezing local judgment.

Dataiku (MLOps) is what they standardized on. Dataiku is a universal AI platform that lets data teams and analysts collaborate on pipelines, models, and governed AI applications. Philip Morris International uses it as the system of record for event streams, with platform engineers as the primary operators and other groups coming in through the same queue.

Leaders get a picture they can actually walk. Teams get fewer mystery statuses. The story is about operating change, not an unpublished percentage.

Value Graph

Philip Morris International uses Dataiku, DocuSign, Twilio, Genesys, Shopify, Red Hat, Hugging Face, OpenAI, Smartsheet, Pega, Zscaler. Shared with Agilent Technologies, American Express GBT, Anglo American, Asahi Kasei, ASE Technology. Industry: Consumer Staples. Value: Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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