


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 saved a lot of money, with 50 to 60% of our cost saved, especially through automation.
I have more time to work on meaningful tasks since automation has been very helpful in automating repetitive and time-consuming tasks.
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 provide very detailed responses that enable us to handle any issues effectively.
Our team manages security and compliance by storing data for five years, archiving logs older than seven days while maintaining backups, and implementing strict logging practices.
The response times were slow to turn around.
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.
It is scalable from the solution perspective.
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.
I found it to be high on stability, and I would rate it at nine.
The solution is generally stable, though we have faced issues with increased transaction loads causing latency and occasional hang-ups.
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.
It was not developed in a consumption-based manner, however, rather in a fixed-price licensing model that did not account for volumes.
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.
The pricing model was not modern, as it wasn't designed on a consumption basis or as a service basis.
The licensing cost can be a bit expensive compared to its competitors.
Overall, my experience with pricing, setup cost, and licensing is that for large organizations and medium organizations, it is very cost-effective.
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.
I find the design studio, where I can build the automation, to be the most useful.
| Product | Mindshare (%) |
|---|---|
| Automation Anywhere | 7.5% |
| SS&C Blue Prism | 2.0% |
| DataRobot | 1.9% |
| Other | 88.6% |



| 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 | 3 |
| Large Enterprise | 8 |
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.
SS&C Blue Prism, renowned for its language capabilities and workflow design, supports detailed automation building, enhancing productivity. Despite some challenges like cost and limited integration, it offers substantial potential in automating diverse processes.
SS&C Blue Prism offers strong capabilities in document reading and a straightforward workflow design, making it accessible with basic BPM knowledge. Detailed automation design in the studio and effective monitoring in the control room are notable features. While facing higher costs and a steeper learning curve, it supports process mining and generative AI initiatives, crucial for industries aiming at transformation and activation services. Limited external system integration and lack of agile delivery encourage a strategic approach in its deployment.
What are the key features?
What ROI should users expect?
SS&C Blue Prism finds its application across industries. In service industries, it automates repetitive tasks while supporting migration projects. Within the insurance sector, it helps automate claims handling and pricing by integrating data efficiently. Companies use it when transitioning processes, such as upgrading systems from older versions to new applications.
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