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Dataiku@Fonterra

How Fonterra Runs Enterprise Reporting on LLM Mesh

Fonterra, a consumer staples organization in New Zealand, uses LLM Mesh from Dataiku to support enterprise reporting for analysts and finance partners.

Fonterra runs enterprise reporting on Dataiku so ownership is obvious when work stalls.

“Consumer Staples work at Fonterra spans more than one site, even when headquarters sits in New Zealand.”
“Analysts and finance partners asked for a shared way to run enterprise reporting without freezing local judgment.”
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Independent write-up. Figures come from public sources or are illustrative.

Value results

CategoryValue result
Risk and complianceAnalysts and finance partners work from the same LLM Mesh record for governed analytics
Risk and complianceGoverned analytics can be reviewed without waiting on a personal export
Risk and complianceNamed workflow replaces ad hoc routing for governed analytics

Story

Consumer Staples work at Fonterra spans more than one site, even when headquarters sits in New Zealand. Governed analytics was splitting across regional habits. Analysts and finance partners asked for a shared way to run enterprise reporting without freezing local judgment.

Dataiku (LLM Mesh) 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. Fonterra uses it as the system of record for governed analytics, with analysts and finance partners 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 The story is about operating change, not an unpublished percentage.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

Fonterra uses Dataiku, Datadog, Microsoft Azure, Red Hat, Stripe, BMC, Snyk, CrowdStrike, Pega, NVIDIA. Shared with Agilent Technologies, American Express GBT, Anglo American, Asahi Kasei, ASE Technology. Industry: Consumer Staples. Value: Risk and compliance. Drag nodes, filter types, or expand a node to follow more commonalities.

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