

Find out in this report how the two AI Finance & Accounting solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
On average, we're saving about 10 to 15 hours per project.
I have seen a return on investment, specifically with increased data science productivity by four times, time saved with deploying models, and homogeneous analysis models developed easily.
It has saved about 20% to 30% of costs.
We have seen a 100% return on investment.
UiPath has reduced human error and saved employee time.
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.
The customer support from DataRobot is proactive and responsive.
They were very helpful, addressing the issue in three hours.
Even though they are external, I can ping them on Slack and I get a response right away, so they really make it very accessible to be in touch.
He works through whatever unique internal environment scenarios we have to overcome to make sure that it's doing exactly what we need, even though we're constantly having new security measures to implement on top of it.
DataRobot's scalability is very strong and grows with my organization's needs.
The solution is capable of scaling with just a few clicks.
The scalability of the UiPath Platform rates a ten out of ten.
From a technical standpoint, it's essential to make the right technical decisions and design a scalable solution.
DataRobot is very stable.
Overall, there was only one instance of downtime in four years, which did not create any significant impact.
I have not experienced any downtime, crashes, or performance issues.
Over six years, we have created zero support cases with UiPath.
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.
Another improvement that DataRobot needs is integrating the capability to modify the whole pipeline with Python.
Adding more AI could help in small tasks that require intelligence or machine learning, leading to the next stage of automation.
If the UI changes or a label is changed, sometimes the whole flow breaks.
Regarding additional functionality for UiPath, I believe that additional features will only come into play when you start talking to the customers, accept feedback, and work on it.
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.
My experience with pricing, setup cost, and licensing reveals that the price points can be improved and DataRobot is not so cost-effective, especially for smaller organizations.
Most of the UiPath products are priced higher than competitors.
The cost can be a barrier in Hungary, making it difficult for me to persuade others to invest, especially when unattended robots come at a significant price point.
When compared to competition, such as Microsoft's Power Automate platform or IBM Cloud Pak, UiPath is expensive.
By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.
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.
When business leaders ask for the fastest possible solution, DataRobot is our go-to platform.
The tool has a noticeable ROI, and the investment is worth every penny as it reduces tedious tasks and improves scalability.
Our use of automation sped up the process of getting paid from insurance companies, saving us substantial amounts of money.
Whenever they release a product, they also release a course in UiPath Academy. So, you can get familiarized with the product and understand the new capabilities.
| Product | Mindshare (%) |
|---|---|
| UiPath Platform | 14.8% |
| DataRobot | 1.7% |
| Other | 83.5% |

| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 1 |
| Large Enterprise | 5 |
| Company Size | Count |
|---|---|
| Small Business | 250 |
| Midsize Enterprise | 143 |
| Large Enterprise | 669 |
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.
UiPath Platform is appreciated for its user-friendly interface and extensive automation capabilities, offering seamless integration with diverse applications. Its intuitive drag-and-drop functionality enables users to design efficient workflows with minimal technical expertise.
UiPath Platform delivers a robust set of features that enhance automation and productivity. With components like Orchestrator, task management is optimized, facilitating better scalability. Users benefit from advanced AI and document understanding tools, boosting data handling accuracy and reducing errors. Despite its strengths, UiPath faces challenges with upgrading processes, AI enhancements, and user documentation. Integration and selector sensitivity issues, along with support and licensing complexities, highlight areas for potential improvement. Users request smoother deployment, error handling, and migration processes. Enhanced support for RHEL/Ubuntu, LINQ, and Lambda and improved real-time insights, automation recording, and scheduling are desired. Streamlining the experience for non-technical users with simplified workflows remains a priority.
What are the key features of UiPath Platform?
What benefits should users look for in reviews?
UiPath Platform is widely implemented across sectors such as finance, healthcare, insurance, HR, IT, and supply chain to automate repetitive business tasks. Common uses include automating data entry, invoice processing, document management, report generation, and customer service operations. Organizations value the platform's ability to integrate seamlessly with systems like SAP, CRM, and Oracle, allowing for enhanced efficiency and accuracy in processing both structured and unstructured data.
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