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Snowflake@Collabro

Collabro Extends Unistore Across Applied Machine Learning

Collabro, an information technology organization in the United States, uses Unistore from Snowflake to support applied machine learning for data scientists and ML engineers.

Value results

CategoryValue result
CapabilityFeature pipelines can be reviewed without waiting on a personal export
CapabilityNamed workflow replaces ad hoc routing for feature pipelines
CapabilityApplied machine learning stays visible to adjacent teams through Unistore

Story

Collabro did not need another dashboard that nobody opened. It needed applied machine learning to move. In the United States, data scientists and ML engineers already knew where feature pipelines went wrong: too many copies, too little ownership, and a close process that waited on the loudest inbox.

Unistore from Snowflake is now in that path. Snowflake is a cloud data platform that separates storage and compute so organizations can share, analyze, and govern data across clouds. The company treats it as production tooling for applied machine learning, which is why data scientists and ML engineers live in it rather than exporting from it once a quarter.

Collabro can show how feature pipelines is handled today. That is the value: a repeatable way to run applied machine learning on software the rest of the industry already recognizes.

Relationship map

Collabro uses Snowflake, Autodesk, Google Cloud, Confluent, Elastic, Box, Synopsys, Microsoft Azure, PTC. Shared with Aviva, FIS, HelloFresh, Jeld-Wen, Matillion. Industry: Information Technology. Value: Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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