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Confluent@Accenture

How Accenture Runs Applied Machine Learning on Apache Kafka

Accenture, an information technology organization in Ireland, uses Apache Kafka from Confluent to support applied machine learning for data scientists and ML engineers.

Value results

CategoryValue result
ProductivityFewer stalled items because feature pipelines has a clear owner
ProductivityHandoffs in applied machine learning sit in a shared queue instead of a mailbox trail
CapabilityNew joiners can see how applied machine learning actually runs

Story

Accenture is based in Ireland and runs information technology operations at a scale where feature pipelines cannot live in side channels. Data scientists and ML engineers were reconciling competing copies of the same work, which slowed applied machine learning and hid who owned the next step.

The company runs applied machine learning on Confluent, with Apache Kafka as the product data scientists and ML engineers actually open. Confluent is the data streaming platform built around Apache Kafka, used to move events between applications in real time. For Accenture, that means data scientists and ML engineers can open one workflow, see feature pipelines, and let neighboring teams join without inventing a parallel stack.

Public materials confirm the companies and products. They do not always publish a single verified KPI for this pairing, so the outcome here is operational: clearer ownership, fewer stalled handoffs, and a shared record for feature pipelines.

Relationship map

Accenture uses Confluent, Servicenow, Google Cloud, Palantir, Anthropic, Twilio, Cartesia, Coupa, Dassault Systemes, Red Hat. Shared with 1Password, Abbott Laboratories, AbbVie, AES, Aisin. Industry: Information Technology. Value: Productivity, Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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