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Great company and team that are vested in your success
April 04, 2024

Great company and team that are vested in your success

Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with DataRobot

We use DataRobot for traditional ML/AI use cases from R&D and training to deploying and monitoring. Use cases include churn / acquisition modelling and other propensity models.
  • AutoML
  • MLOps
  • Speed-to-market
  • Deeper / better integration with hyperscalers
  • Increased velocity of model development and deployment 3X
  • Increased revenue through deployment of specific models that have a direct tie to revenue generation.
It is VERY friction-less and you don't have to worry about stitching a bunch of services together as with the hyperscalers. It just works and is very comprehensive from Dev to Ops.
Agent retention and growth. DataRobot's propensity models have impacted this KPI significantly.
DataRobot is more friction-less and comprehensive enough to tackle a majority of our use cases.

Do you think DataRobot delivers good value for the price?

Yes

Are you happy with DataRobot's feature set?

Yes

Did DataRobot live up to sales and marketing promises?

Yes

Did implementation of DataRobot go as expected?

Yes

Would you buy DataRobot again?

Yes

If you're starting to build out your Data Science + ML/AI team this is the platform which will jump start you and get you from 0 to 1 much faster compared to doing things natively within the hyperscaler eco-system.

For very complicated use cases or where you need hundreds of models at a micro geo level the licensing may become cost prohibitive.

DataRobot Feature Ratings

8.7
Connect to Multiple Data Sources
8
Extend Existing Data Sources
8
Automatic Data Format Detection
10
9.0
Visualization
9
Interactive Data Analysis
9
8.0
Interactive Data Cleaning and Enrichment
8
Data Transformations
8
Data Encryption
8
Built-in Processors
8
9.3
Multiple Model Development Languages and Tools
8
Automated Machine Learning
10
Single platform for multiple model development
10
Self-Service Model Delivery
9
9.5
Flexible Model Publishing Options
10
Security, Governance, and Cost Controls
9