


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.
In terms of cost, we participated in projects achieving two to three million dollars in annual savings.
As a return on investment, we have achieved a 250% ROI in six to nine months, and sometimes it increases up to 380% percent.
Automation Anywhere has helped us save money.
Previously we had five employees doing the entire workflow, and now we can do it with two employees because agents are being used to do the same which was previously being done by the employees.
For team productivity, a single ML engineer using DataRobot is equivalent to five to ten traditional ML engineers.
On average, we're saving about 10 to 15 hours per project.
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.
Whenever we need help, we can reach out to them, and they help us out.
We also have dedicated account managers and technical experts to solve our problems related to Automation Anywhere.
We just have to raise a ticket, after which we receive a call, email, or ping from the Automation Anywhere team.
If you are paying somewhere between $100,000 to $200,000 annually, you receive a dedicated technical account manager who understands your AWS setup and models, unlike generic ticketing systems.
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.
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.
As we are using Microsoft Copilot for our AI agents, I look forward to integrating it with Automation Anywhere and its solutions, seeing it as a beneficial partnership as Automation progresses toward AI as the main solution.
The centralized control room allows us to orchestrate and manage bots seamlessly.
I can scale it in terms of hundreds of bots and configure hundreds of parallel robots easily.
Scalability is where DataRobot truly excels; it manages to handle millions or even billions of rows using technologies such as Spark and Dask for distributed training.
DataRobot's scalability has allowed us to reduce the number of employees needed for model creation.
DataRobot is very scalable because the customer initially started with two licenses, and now they have around 20 licenses.
We run our automations on dedicated Azure VMs, and when we needed to increase the number of unattended licenses, it was just a matter of acquiring those licenses and spinning up new VMs for the additional automations.
The framework provided allows for building scalable and reliable bots that meet non-functional requirements.
Scaling the same process to multiple machines just involves assigning users and adding the machines to the templates, making it an easy process.
With the latest applications, there are no significant issues like freezing or crashing.
From a stability and reliability perspective, we can remain confident that the product performs as an enterprise solution and meets expected standards.
If you have good best practices, reusable code, an effective framework, and a solid development methodology, bots can be very stable.
Model stability is also reinforced through drift detection and auto-alerts if data changes or model accuracy dips, catching issues before they impact business operations.
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.
It is better to write a Python script instead of using Automation Anywhere's package when dealing with Excel because it is buggy and tends to break.
Making the product more lightweight by reducing its dependency on infrastructure could greatly help in the long run.
It would be beneficial if the platform provided options for power developers to integrate seamlessly with languages like Java or C#, allowing them to write their own scripts and code.
If DataRobot also adds those data transformation capabilities, then it will be an end-to-end tool and the customer will not have to procure many tools for doing the ingestion and transformation process.
The integration of DataRobot would greatly benefit from allowing more realistic tools and would be improved if it integrates more comprehensively with AWS cloud and other cloud platforms.
For API deployment, we require enhanced data systems, including procuring new servers for GPU support.
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.
It is more cost-efficient compared to all other RPA platforms.
Automation Anywhere costs are aligned with UiPath and Blue Prism, which are also expensive.
It is not cheap, with costs ranging between 700 to 800 dollars per month.
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.
The annual platform license ranges from around $100,000 to $500,000, typically starting at $100,000 per year for small teams with one to two users.
It is a bit expensive but remains very effective.
Comparing it with other RPA tools, the licensing cost can be high, which is especially challenging for small businesses.
from what I have heard and seen, it is probably more expensive than other vendors, but there are no doubts that it is worth it.
Overall, I describe UiPath Platform as providing good value for enterprise automation, with simple licensing structures, clear packaging of AI capabilities, and enhanced productivity justifying the costs associated with usage.
I can set it up to provide users with a form to fill in all required information, and then the bot operates based on those specifications.
For example, the email module has been enhanced over the years to support all the latest authentication technologies. That is very important as we move away from username and password and embrace multi-factor authentication.
Automation Anywhere has undergone drastic changes over the past five years, transitioning from version 10 to A360, including desktop-based and cloud-based options.
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.
The automated machine learning and AI features of DataRobot have helped us build predictive models rapidly using hundreds of algorithms.
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 (%) |
|---|---|
| Automation Anywhere | 7.5% |
| UiPath Platform | 7.7% |
| DataRobot | 1.9% |
| Other | 82.9% |


| Company Size | Count |
|---|---|
| Small Business | 157 |
| Midsize Enterprise | 82 |
| Large Enterprise | 558 |
| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 1 |
| Large Enterprise | 10 |
| Company Size | Count |
|---|---|
| Small Business | 256 |
| Midsize Enterprise | 149 |
| Large Enterprise | 693 |
Automation Anywhere offers ease of use, robust system connectivity, and GenAI-driven document automation through a cloud-native platform, significantly enhancing productivity across multiple industries with advanced AI features.
Delivering a comprehensive suite of tools designed for easy integration and rapid deployment, Automation Anywhere drives efficiency by reducing costs and automating repetitive tasks. Its cloud-native platform supports broad industry adoption, including advanced AI features like process automation and Co-Pilot, streamlining complex workflows with minimal technical skills required. Users benefit from robust integration capabilities, which facilitate seamless interaction with multiple systems. However, there is room for improvement in areas such as user-friendliness for beginners, stability, flexible licensing, and enhanced OCR functionality. Organizations in sectors such as banking, finance, manufacturing, and healthcare gain from the improved operational efficiency and ROI Automation Anywhere offers.
What are the important features of Automation Anywhere?
What benefits should be evaluated in reviews?
In the insurance industry, Automation Anywhere is utilized for automating processes such as enrollment management and compliance checks. Its applications extend to supply chain management, financial transactions, and business performance monitoring across sectors like banking, finance, manufacturing, and healthcare, helping organizations to automate routine tasks, improve efficiency, and reduce costs.
DataRobot automates model building and deployment, simplifying MLOps with user-friendly interfaces. Its AutoML and feature engineering streamline model comparison, selection, and testing, enhancing efficiency and scalability.
DataRobot facilitates efficient integration with cloud systems and data sources, reducing manual workload, enhancing productivity, and empowering data-driven decision-making. Its strengths lie in automating complex modeling tasks and supporting multiple predictive models effectively. Users emphasize the need for better handling of large datasets, integration with orchestration tools, and more flexibility for custom code integration and advanced model tuning. They also seek improved support response times, transparent model processing, real-world documentation, and enhanced capabilities in generative AI and accuracy metrics.
What are the key features of DataRobot?DataRobot is adopted across industries like healthcare and education for creating and monitoring machine learning models. It accelerates development with GUI capabilities, aids data cleaning, and optimizes feature engineering and deployment. Organizations can predict behaviors, automate tasks, manage production models, and integrate into data science processes to improve data processing and maximize efficiency.
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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