Apps Run The World Apps Purchases

Customer	Industry	Empl.	Revenue	Country	Vendor	Application	Category	When	VAR/SI	Insight Source
Rochester City School District	Education	5800	$954M	United States	The Trade Desk	The Trade Desk	Digital Advertising Platform	2021	n/a
University of Washington	Education	35331	$7.1B	United States	Databricks	Databricks MLflow	ML and Data Science Platforms	2020	n/a	In 2020, University of Washington implemented Databricks MLflow within its ML and Data Science Platforms environment. The deployment targeted standardization of experiment tracking and model lifecycle management to support campus research computing and institutional data science teams. The implementation used Databricks MLflow core capabilities, including experiment tracking, Projects for packaging reproducible runs, the Models component for artifact capture, and a centralized model registry to record metadata and versioning. Configuration integrated MLflow with Databricks notebook and compute workflows so code, metrics, parameters, and artifacts were logged consistently across research experiments. Databricks MLflow was operated with built-in integrations for Tensorflow, PyTorch, scikit-learn, H2O.ai and Amazon Sagemaker, allowing models built in those frameworks to be tracked, registered, and prepared for downstream serving or export. Operational coverage emphasized research labs and university data science groups, aligning model development and experiment management with academic analytics and cross-disciplinary research projects. Governance focused on reproducibility, artifact version control and registry-based model promotion workflows to enforce provenance and handoffs between researchers and productionization channels. University of Washington is also named among organizations using and contributing to MLflow, reflecting both internal use of Databricks MLflow and participation in the broader MLflow community and standards.
	Education	48	$5M	United States	Apollo.io	Apollo.io	Marketing Automation,Sales Engagement	2019	n/a
	Education	1200	$450M	United States	Bigtincan	Bigtincan ClearSlide Sales Engagement Platform	Sales Engagement	2018	n/a
	Education	12050	$1.9B	United States	Bigtincan	Bigtincan ClearSlide Sales Engagement Platform	Sales Engagement	2018	n/a
	Education	4500	$240M	United States	Cirrus Insight	Cirrus Insight For Salesforce	Marketing Automation,Sales Engagement	2018	n/a
	Education	12050	$1.9B	United States	Cirrus Insight	Cirrus Insight For Salesforce	Marketing Automation,Sales Engagement	2017	n/a
	Education	31987	$11.6B	United States	Cirrus Insight	Cirrus Insight For Salesforce	Marketing Automation,Sales Engagement	2016	n/a
	Education	500	$50M	United States	Groove Labs	Groove Platform	Sales Engagement	2019	n/a
	Education	5000	$440M	United States	Insightly	Insightly CRM	CRM	2014	n/a

Logo

Customer

Industry

Empl.

Revenue

Country

Vendor

Application

Category

When

VAR/SI

Insight

Insight Source

Rochester City School District

Education

5800

$954M

United States

The Trade Desk

Digital Advertising Platform

2021

n/a

University of Washington

Education

35331

$7.1B

United States

Databricks

Databricks MLflow

ML and Data Science Platforms

2020

n/a

In 2020, University of Washington implemented Databricks MLflow within its ML and Data Science Platforms environment. The deployment targeted standardization of experiment tracking and model lifecycle management to support campus research computing and institutional data science teams. The implementation used Databricks MLflow core capabilities, including experiment tracking, Projects for packaging reproducible runs, the Models component for artifact capture, and a centralized model registry to record metadata and versioning. Configuration integrated MLflow with Databricks notebook and compute workflows so code, metrics, parameters, and artifacts were logged consistently across research experiments. Databricks MLflow was operated with built-in integrations for Tensorflow, PyTorch, scikit-learn, H2O.ai and Amazon Sagemaker, allowing models built in those frameworks to be tracked, registered, and prepared for downstream serving or export. Operational coverage emphasized research labs and university data science groups, aligning model development and experiment management with academic analytics and cross-disciplinary research projects. Governance focused on reproducibility, artifact version control and registry-based model promotion workflows to enforce provenance and handoffs between researchers and productionization channels. University of Washington is also named among organizations using and contributing to MLflow, reflecting both internal use of Databricks MLflow and participation in the broader MLflow community and standards.