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storySaudi ArabiaEnergyProductivityRisk and complianceCapability

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Confluent@Saudi Aramco

How Saudi Aramco Runs Applied Machine Learning on Apache Kafka

Saudi Aramco, an energy organization in Saudi Arabia, uses Apache Kafka from Confluent to support applied machine learning for data scientists and ML engineers.

Value results

CategoryValue result
ProductivityHandoffs in applied machine learning sit in a shared queue instead of a mailbox trail
Risk and complianceApache Kafka is the governed place data scientists and ML engineers use for applied machine learning
CapabilityNew joiners can see how applied machine learning actually runs

Story

Energy work at Saudi Aramco spans more than one site, even when headquarters sits in Saudi Arabia. Feature pipelines was splitting across regional habits. Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.

Confluent (Apache Kafka) is what they standardized on. Confluent is the data streaming platform built around Apache Kafka, used to move events between applications in real time. Saudi Aramco uses it as the system of record for feature pipelines, with data scientists and ML 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 The story is about operating change, not an unpublished percentage.

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Saudi Aramco uses Confluent, Genesys, HubSpot, Autodesk, Twilio, BMC, Hexagon, Proofpoint. Shared with 1Password, Abbott Laboratories, AbbVie, Accenture, AES. Industry: Energy. Value: Productivity, Risk and compliance, Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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