

DataRobot and Devo cater to different needs in AI and data analytics. Users generally find the feature set of Devo superior, while DataRobot's pricing and support receive higher satisfaction scores. Despite this, Devo's enriched features outweigh its higher price.
Features: DataRobot offers automated data preparation, predictive modeling, and deployment, which is comprehensive. Devo excels in real-time data analytics and visualization, scoring higher for its integration capabilities. Users highlight Devo's advanced analytics as more valuable, though both platforms have robust feature sets.
Room for Improvement: Users of DataRobot point out the need for enhanced customizability and more intuitive tools for non-technical users. Devo users suggest improvements in documentation and more streamlined onboarding processes. DataRobot's feedback emphasizes usability improvements, while Devo focuses on user experience enhancements.
Ease of Deployment and Customer Service: DataRobot is praised for its straightforward deployment process and responsive customer service. Devo's deployment is slightly more complex due to its advanced features, but it also has commendable support. DataRobot has an edge in ease of deployment, while both provide reliable customer service.
Pricing and ROI: DataRobot is rated favorably for its competitive pricing and clear ROI, making it attractive for budget-conscious buyers. Devo's pricing is higher, but users believe its feature set justifies the cost, providing substantial ROI. DataRobot's lower cost appeals to many, but Devo's advanced features deliver considerable value for the investment.
On average, we're saving about 10 to 15 hours per project.
They answer all my questions and share guidance on using DataRobot scripts if certain functionalities are not available in the UI.
Being cloud-hosted enables automatic resource scaling, which supports collaboration across teams.
DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python.
There is a lack of transparency in the models; sometimes it feels like a black box.
Integrations with other sandboxes could be improved to better interpret data using AI and machine learning models.
The setup cost was minimal because it's cloud-hosted, eliminating the need for heavy on-premises infrastructure, allowing us to start using it immediately after purchase.
DataRobot has positively impacted our organization in many ways. First, it has improved efficiency; tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours.
By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.
When they see a spike in a line chart for a failed login, which could be a true or false attempt, they can click that spike, and a table widget on the same active board instantly populates with raw logs of data for those specific failed logins.
| Product | Market Share (%) |
|---|---|
| DataRobot | 1.0% |
| Devo | 1.1% |
| Other | 97.9% |

| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 4 |
| Large Enterprise | 11 |
DataRobot captures the knowledge, experience and best practices of the world’s leading data scientists, delivering unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users to build and deploy highly accurate machine learning models in a fraction of the time.
Devo is the only cloud-native logging and security analytics platform that releases the full potential of all your data to empower bold, confident action when it matters most. Only the Devo platform delivers the powerful combination of real-time visibility, high-performance analytics, scalability, multitenancy, and low TCO crucial for monitoring and securing business operations as enterprises accelerate their shift to the cloud.
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