RPA buyer’s guide: Top 24 robotic process automation tools available today

Robotic process automation (RPA) explained

Robotic process automation (RPA) can streamline business workflows by eliminating tedious manual tasks without requiring you to completely re-engineer legacy systems.

Even the modern workplace can be boring and repetitive. Enter robotic process automation (RPA), a smart set of tools that deploys AI and low-code options to simplify workflows and save everyone time while also adding safeguards that can prevent costly mistakes.

[ Download our editors’ PDF robotic process automation (RPA) buyer’s guide today! ]

RPA is an application of technology, governed by business logic and structured inputs, aimed at automating business processes. Using RPA tools, a company can configure software, or a “robot,” to capture and interpret applications for processing a transaction, manipulating data, triggering responses, and communicating with other digital systems.

In some organizations, RPA is a way to modernize old software without replacing it. Most organizations have business applications that work perfectly well but require users to click on the same boxes in the same patterns all day long. RPA tools aim to replace that tedium, adding a new layer to automate repetitive tasks without having to reinvent the application at the core.

RPA is also a relatively simple way to integrate AI algorithms into old applications. Many RPA platforms offer computer vision and machine learning tools that can guide the older code. Optical character recognition, for example, might extract a purchase order from an uploaded document image and trigger accounting software to deal with it. The ability to suck words and numbers from images are a big help for document-heavy businesses such as insurance or banking.

The biggest benefit, however, may be how RPA tools are “programmed,” or “trained” — a process by which the platforms’ robots “learn” watching business users click away. This job, sometimes called “process discovery,” can use a click stream to imitate what your users just did — similar to how spreadsheet macros can be created.

Still, RPA isn’t automatic. Manual intervention and tweaking is necessary during training. Sometimes code must be written to handle what can’t be achieved by a preconfigured bot. But you won’t have to do much of this. Moreover, the bots keep getting smarter, making training easier and edge cases less frequent. AI routines can also help look for patterns that may speed up the bots in the future.

In this buyer’s guide

• Robotic process automation (RPA) explained
• What to look for in robotic process automation (RPA) tools
• Leading vendors for robotic process automation (RPA)

What to look for in robotic process automation (RPA) tools

Before you commit to an RPA product, you need to understand that every single one of them uses its own proprietary file formats. Despite their utility, they’re all roach motels, completely lacking in portability. It’s not like they’re ignoring the standards: There are no standards. Evaluate carefully and do a proof of concept before committing your company to a rollout, because changing your mind later will be painful and expensive.

Verify that all basic features — and the differentiating features you think you’ll need — work in your environment. Build scripts using all the supplied tools and demonstrate that the orchestration works properly. Test out an unattended bot, verify that bots can parse your unstructured documents and PDFs, and go through process mining procedures.

Pay particular attention to these key factors in your evaluation:

Ease of bot setup: There should be a range of ways to set up a bot for different personas. Business users should be able to point and click the applications they normally use while a recorder takes note of the actions. Citizen developers should be able to use a low-code environment to define bots and business rules. And finally, professional programmers should be able to write real automation code that calls the RPA tool’s APIs.

Low-code capabilities: Typically, low-code development is a combination of drag-and-drop timeline construction from a toolbox of actions, filling out property forms, and writing an occasional snippet of code. Writing small amounts of code, for example “loan_amount < 0.20 * annual_income” can be much quicker than graphical methods of specifying a business rule.

Attended vs. unattended: Some bots make sense only if they run on-demand (attended) when a business user needs them to perform a well-defined task — for example, “turn this graphic into text and put it on the clipboard.” Other bots make more sense if they run in response to an event (unattended), such as “perform due diligence on each loan application submitted from the website.” You need both kinds of bots.

Machine learning capabilities: The RPA tools of just a few years ago had trouble extracting information from unstructured documents — and typically, 80% of a company’s information is found in unstructured documents rather than in databases. These days, it’s common to use RPA machine learning capabilities to parse documents, find the required numbers, and return them to the user. Some vendors and analysts call this hyperautomation, but the fancy language doesn’t change the functionality.

Exception handling and human review: Categorical machine learning models typically estimate the probabilities of the possible results. For example, a model to predict loan defaults that returns a 90% probability of default could recommend denying the loan, and one that calculates a 5% probability of default could recommend granting the loan. Somewhere in between those probabilities there’s room for human judgment, and the RPA tool should be able to submit the case for review.

Integration with enterprise applications: A bot isn’t much good to your company if it can’t get information out of your enterprise applications. That’s usually easier than parsing PDFs, but you need drivers, plug-ins, and credentials for all your databases, accounting systems, HR systems, and other enterprise applications.

Orchestration and administration: Before you can run any bots, you need to configure them and supply the credentials they need to run, typically in a secure credential store. You also need to authorize users to create and run your bots — and provision your unattended bots to run on specific resources in response to specific events. Finally, you need to monitor the bots and direct exceptions to humans.

Cloud bots: When RPA started out, RPA bots exclusively ran on user desktops and company servers. But as IT estates have grown into the cloud, companies have set up cloud virtual machines for use by bots. Recently, some RPA companies have implemented cloud-native bots that run as cloud apps using cloud APIs rather than running on Windows, macOS, or Linux virtual machines. Even if your company has invested little in cloud applications today, it will eventually, so this capability is highly desirable.

Process and task discovery and mining: Figuring out your processes and prioritizing them for automation is often the most time-consuming part of implementing RPA. The more the RPA vendor’s app can help you mine processes from system logs and construct task flows by observation, the easier and quicker it will be to start automating.

Scalability: As your RPA implementation rolls out to the enterprise and handles more automations, you can easily run into scalability issues, especially for unattended bots. A cloud implementation, whether native, in virtual machines, or in containers, can often mitigate scalability issues, especially if the orchestration component is capable of provisioning additional bots as needed.

Ultimately, the success or failure of your RPA implementation will depend on identifying the highest-reward processes and tasks for automation. For example, if the highest-reward process for a bank is performing due diligence on loan applications, make that (or a key task from that process) your RPA proof of concept.

Also, don’t cut corners on your testing cycle. If it turns out the RPA solution you’ve adopted has some missing or inadequate capability, and you need to switch, you’re in for a world of hurt. To mitigate the risk of having to re-create all your bots from scratch, you should document all the steps in each task and process. When you change horses, you might still need to spend a week re-implementing each bot, but you can avoid the month you spent figuring out each process.

Leading vendors for robotic process automation (RPA)

While there are dozens of RPA vendors, the same ones enter into the discussion again and again. The following seven vendors have been selected from the recent Forrester Wave and Gartner Magic Quadrant analyst reports and arranged alphabetically. Note: Inclusion in this list is not a recommendation, and exclusion is not a condemnation.

Airslate: Document-centric tasks such as PDF editing or generating e-signatures for contracts are one of the focuses for Airslate. The bots for simplifying the workflow are programmed with the drag-and-drop Flow Creator. Preprogrammed resources include connections to major back ends such as Salesforce as well as a collection of templates for common processes.

• Major features: Document editing and signature tracking
• Major use cases: Contract and agreement processing

Appian: Appian acquired Jidoka in 2020 and changed the product’s name to Appian RPA while integrating it with its Digital Process Automation suite. Jiodka is a Japanese term that might be translated as “automation with a human touch,” a reference to how its software robots are trained to emulate humans interacting with the standard systems — mainframe terminal, web, databases, and so on. Appian RPA’s low-code integrated development environment (IDE) encourages fast creation of custom bots, while the dashboard tracks all the operating robots and can create a video of the screen to help debug the bots deployed across Appian’s cloud. The information is ingested into what they call a “data fabric” filled with not just numbers and letters, but relationships between elements. Deeper integration across both desktop platforms and mobile brings their tool to the edges of any enterprise network.

• Major features: Java-centric bots offer cross-platform range
• Major use cases: Client management and compliance paperwork processing

Automation Anywhere: The Bot Store at Automation Anywhere offers a collection of tools for the Automation 360 platform that perform standard clicking and tracking as well as processes that glue together complex data files. There are bots for extracting information from spreadsheets, files, or web pages, and bots for storing this information in databases for issue tracking, invoice processing, and more. Many of the bots rely on APIs such as Microsoft Azure’s image analysis API. One of the goals is opening up access across the enterprise with easy-to-automate tools such as AARI, which can turn any web application into an automated worker. Automation Anywhere also offers a “community edition” that is free for small businesses with a limited workflow, and a cloud-based service, saving you the trouble of installing and maintaining the RPA itself.

• Major features: The Center of Excellence (CoE) manager tracks the performance of the various bots in a centralized dashboard; Bot Insight drills down to track the performance of each bot
• Major use cases: Opening up bot development and deployment across the enterprise

AutomationEdge: The bots at AutomationEdge offer hyperautomation through a mixture of API interaction and AI. The focus is interacting with web pages, databases, and Excel spreadsheets. Its Conversational RPA brings a natural language interface to many interactions. Many bots in the bot store are preconfigured for specific industries or sections of a business, such as human resources or customer relations. AutomationEdge also offers a free version that’s limited in time, steps, and reach. Some AI-driven options such as the Conversational RPA and Intelligent Document Processing aren’t included. A cloud-based service is also available for those who don’t want to install it.

• Major features: Pay-as-you-go pricing simplifies adoption
• Major use cases: Chatbot management; front-, middle-, and back-office document processing

AWS Lambda: The Amazon Web Services cloud is filled with options for data processing. Lambda functions act like logical glue for connecting services and automating work flowing through their networks. The functions can be as small or as large as needed and they can be triggered when new data arrives. Lambda functions are aimed more at automating work on the back end, and they are most efficient when working with AWS services but can be connected to any service with extra work.

• Major features: Automating back-end data flows in the Amazon cloud
• Major use cases: Fixing problems and smoothing data movement between services

Cyclone Robotics: The Cyclone tool set is growing into a broad selection of tools that support low-code and not-so-low-code development. Its RPA Studio brings together basic automation tools for building data pipelines with advanced AI tools for OCR and computer vision. It also offers a low-code option for integrating multiple tools into a cohesive, automated workflow. Small and midsize businesses can also run the tools in Cyclone’s cloud using the EasyPie service.

• Major features: Built for the Chinese market with a wide range of plugins tackling major platforms and services with AI
• Major use cases: A wide range of markets, including mobile

Datamatics: TruBots, the name Datamatics gives its individual programs, are created with TruBot Designer, a tool that lets you create and edit the software. Much of the work is accomplished by dragging and dropping components in a visual designer, but developers can also adjust the system-generated code in an IDE. The bots can be coordinated with TruBot Cockpit, and the system emphasizes text processing with special tools for scanning images and making sense of unstructured text. The tool runs in the cloud but some features can be installed on your own machine with a personal edition for handling more personal tasks, something Datamatics calls the “democratization of RPA.” Teams with document-heavy workloads can use TruCap, a tool for template-free data ingestion.

• Major features: Integration with AI for OCR and language analysis; mainframe integration; desktop version
• Major use cases: Chatbot and call center support; desktop automation

EdgeVerve Systems: The AssistEdge system helps build out your data processing infrastructure by integrating with major data sources and tracking users to discover common work patterns with AssistEdge Discover. Call centers and customer help portals can use AssistEdge Engage to automate the repetitive tasks of orchestrating multiple legacy systems. When possible, Infosys subsidiary EdgeVerve relies on AI to provide contextual help and process incoming forms and other data. The document processing system, XtractEdge, for instance, offers OCR to speed form processing. The company also has systems optimized for industries such as supply chain management (TradeEdge) or banking. It offers migration from desktop to a cloud solution, and an open-source edition.

• Major features: Open-source edition; tighter integration with AI for contextual and visual processing
• Major use cases: Supply chain management, financial transactions

Fortra Automate: The RPA tools from Fortra (formerly HelpSystems) tackle business tasks ranging from responding to inquiries to generating reports. The core Desktop Automation tool scrapes data sources and interacts with web apps and local software by simulating events in the Windows GUI. There’s an emphasis on Microsoft Office tools to produce reports, both textual and graphical, consumed while managing a business. Larger jobs that span multiple desktops can use Automate Plus and Automate Ultimate for added scale. Document scanning is performed with Automate Intelligent Capture. All integrate security and audit capabilities to help managers after development.

• Major features: Integration with Microsoft desktop applications
• Major use cases: Claims processing, service industries

IBM Automation: IBM offers a wide range of options for automating menial tasks, split into separate products, and bundled under the umbrella of IBM Automation. IBM Cloud Pak for Business Automation, for example, provides a low-code studio for testing and developing automation strategies. AI tools provide optical character recognition for documents. The Watson Assistant provides customer care with integrated bots. Teams can iterate over the workflows and explore hypothetical strategies with the Processing Mining tools. All the software can be deployed locally or in IBM’s cloud.

• Major features: Deep experience with enterprise workflow; integration with many mainframes
• Major use cases: Data capture, scientific process management; business decision automation, front-line customer care

ImageTech Systems Kofax: Kofax is a set of bots for document processing and workflow automation. Its Design Studio offers an IDE for turning code written in Java, Python, or another programming language into instructions for their bots. Some users will want to use its Automated Process Discovery code for tracking existing workflows and producing bots. Code can also be spun off into smaller tools called Kapow Kapplets that handle focused chores locally. All the behavior is tracked with standard analytics and reported through a dashboard so you can watch for robotic glitches.

• Major features: Integration with enterprise content management tools; microapps platform to simplify deployment
• Major use cases: Managing content collections; data pipeline integration

Laiye: Laiye is another platform emerging from the Chinese marketplace to target retail groups and others with extensive customer requirements. The Automation Creator is a drag-and-drop IDE for turning workflow into Robots that can be deployed and tracked with tools like the Creativity Center.

• Major features: AI-powered chatbots and a cloud-native robots
• Major use cases: The Work Execution System offers general support for document-centric business tasks

Microsoft Power: The Power Automate tool from Microsoft is part of the company’s Power platform for creating apps, virtual agents, and BI reports. The Desktop tool focuses on automating common Windows 10 (and higher) operations while the Cloud tool handles server-side tasks. The user-friendly interface enables everyone to track their workflow and convert it into an automated, editable routine. Power Advisor tracks statistics about performance to locate bottlenecks and other issues. Microsoft is integrating some of its AI into Power. Users can build new Automation scripts with natural language by describing what should happen. AI Builder can also create and deploy models that make predictions and even decisions, taking more work off of users’ shoulders.

• Major features: Focus on Windows 10 or 11 platform on the desktop or on Azure
• Major use cases: Broad, enterprise-wide empowerment; AI integration

Nice: The Nice robots are designed to run as supervised assistants for humans or, if they’re competent enough, as unsupervised back-office tools. The goal is “journey orchestration” so customers or staff are helped along at each step of the digital pipeline. One assistant Nice Virtual Employee Assistant (NEVA), is billed as a friendly assistant and “workforce multiplier” for customer service issues. The Scene Composer for the Real-Time Designer can track how clicks and keystrokes interact with web pages. Data from other sources can be gathered through Connectors to standard back-office sources such as SAP, Siebel, and .Net servers. Its CXexchange offers hundreds of extensions and agents that speed integration. CXone, its open cloud platform, helps support this growth around the globe.

• Major features: Integration between desktop assistants and server-side back end
• Major use cases: Call center automation; customer service tools; speeding workflow by creating robots that first learn by assisting humans before graduating to full autonomy in the back office

Nintex: The RPA tools from Kryon are now part of the Nintex data automation constellation, creating a complete platform for managing processes and business workflows. Process Discovery helps find the work that needs to be automated and turned into bots that can be deployed and tracked. For document-heavy processes that may require signatures, Nintex’s collection of RPA bots focuses on integration with Microsoft 365, Salesforce, and Adobe tools to automate the process of creating documents and signing them in a digitized legal pipeline. The results can run either in the cloud or on premises.

• Major features: Tight integration with dominant desktop tools
• Major use cases: Compliance pipelines dominated by documents

NTT-AT WinActor: NTT Advanced Technology’s WinActor was built to save Windows users time by automating the most common steps. It integrates with major Microsoft tools to build sophisticated workflows by recording user actions. These are turned into scenarios, and users can trigger these scenarios when a new event occurs such as the arrival of an email. A new request for information, for instance, can be turned into a qualified lead for the sales database with a few clicks. A wide variety of supplemental libraries can extend the tool to handle specific tasks such as creating PDF versions.

• Major features: Heavy integration with Microsoft tools
• Major use cases: Email processing and database integration; spreadsheet automation

Pega: Pega (aka Pegasystems) offers a wide variety of tools that speed up integration and processing for enterprises, including AI classifiers, chatbots, devops support tools, and pure RPA. Creating the right automation can begin with Pega’s AI-driven workforce intelligence tool, a bot that installs on desktops to track how people work. This survey will reveal bottlenecks where poor back-end processing can be automated now and in the future. Pega wants to deliver “self-healing” and “self-learning” applications that can use AI and other statistics to recognize new opportunities for better automation. Pega supports common use cases such as reconciling financial transactions and onboarding new customers. The company also offers low-code options for BPM.

• Major features: Fully integrated with suite of enterprise tools for developing, deploying, and automating data processing
• Major use cases: Regulatory compliance and integration

Rocketbot: Juggling documents with Python-based bots on Linux, Mac, or Windows desktops is the main focus of Rocketbot. Text can be extracted using Rocketbot Telescope and then fed into backed data using bots trained by Rocketbot Studio’s drag-and-drop editor. Rocketbot Orquestador will manage them, running them as needed while compiling statistics.

• Major features: Python-based bots
• Major use cases: Document processing and data extraction

Salesforce MuleSoft RPA: The Mulesoft RPA tool from Salesforce, once known as Servicetrace, is now part of a larger platform for workplace automation and enterprise architecture. The RPA tools use AI and machine learning to help decode documents and automatically collect data. Automation can be scripted with the drag-and-drop RPA Builder, which brings wizard-driven solutions, or collected automatically with RPA Recorder, which watches users to capture repetitive tasks. When the results are deployed with the bot Manager, the system’s vertical scaling enhances parallel operations enabling multiple bots to run simultaneously. 

• Major features: AI-based OCR and a good editor encourages development; recent merger will bolster integration with API-based workflows
• Major use cases: Banking, utilities, and other industries with heavy compliance-driven work

Samsung SDS Brity RPA: Samsung SDS’s Brity RPA is split into three parts. Designer offers drag-and-drop flowcharting for both desktop and enterprise back-end legacy services through a variety of connectors. Bot schedules and runs the various jobs at preset times or in response to events, rebooting virtual machines and simulating all events that might be generated by a real human. Bigger, more independent jobs can be split off to run in the Bot processor. Samsung SDS is also integrating a wide variety of AI routines (machine learning, natural language processing, visual, and analytic ) and is expanding to deliver collaboration software for teams.

• Major features: Aimed at improving industrial and enterprise business flow through automation
• Major use cases: Time-saving and quality improvement for enterprise-driven tasks

SAP: SAP offers an RPA option to simplify many of the workflow operations with its software. SAP’s tool can watch teams to imitate their actions. When it’s done, you can tweak the process in a drag-and-drop low-code IDE. The results are deployed into the SAP environment to live as either attended or unattended bots. Teams that want to leverage the work of others can turn to the SAP RPA store to download bots for common tasks such as unpacking Excel spreadsheets looking for orders to recognize and categorize.

• Major features: Integration with the SAP stack
• Major use cases: Automating the business processes tracked and driven by SAP

SS&C Blue Prism: SS&C Blue Prism, one of the earliest RPA companies (it began in 2012), pushes “intelligent automation” that mixes more AI into the process to simplify scaling and adaptive processes. The emphasis is on using AI and machine learning to “create journeys” for your data as it’s handed off along a chain of bots that often make fully automated decisions through sophisticated machine learning algorithms. You string together a sequence of actions at the beginning, but then each action generates statistics that can be used to train and improve the choices made. The company also maintains a digital exchange where third-party plugins and add-ons can be purchased to extend the powers by creating connections with traditional databases such as MySQL, larger providers such as AWS, and social media outlets such as Twitter.

• Major features: Big investment in AI, including machine vision and sentiment analysis for classifying and responding to all messages
• Major use cases: Building a full chain of document and message processing

UiPath: UiPath offers a full collection of tools for discovering workflows through Process Mining and Task Analysis and turning them an autonomous processes that can be edited and tweaked. These robots are controlled by Orchestrator, which triggers them in response to events while tracking behavior, generating reports, and controlling access where needed for compliance. UiPath is expanding into AI and is emphasizing machine vision tools that can extract information from images or screenshots. These are often focused on OCR to convert letters and numbers into machine-understandable forms.

• Major features: Open environment allows integration of VB.Net, C#, Python, and Java code when challenges grow
• Major use cases: Integration with full legacy stack solutions; transaction processing

WorkFusion: The digital workers from WorkFusion come with individual human names and special focuses. Tara, for instance, is a “top OFAC/AML expert laser-focused on keeping your transactions risk-free.” Casey is a customer relations specialist “obsessed with creating a better, faster customer experience.” Enterprises can begin with them as a starting point or create a custom version that can deploy OCR and some AI to their particular tasks. The digital workers are deployed with Workforce Enterprise to either run autonomously or work as assistants for humans that remain in the loop.

• Major features: Digital workers tuned to common roles for RPA and workforce automation.
• Major use cases: Email and client interaction; task routing

Open source tools: The major companies are generally selling proprietary tools, although so-called community editions with limited functionality are common. Open source RPA processes are less common but you can often accomplish many of the simple tasks by stringing together some open source projects. You are likely going to have to do much more work to train the tools yourself, often by typing code into an editor. Still, they remain an interesting option. Check out Puppeteer, Selenium, and headless Firefox for a basic start.

• Major features: Full open source access to code; no vendor lock-in
• Major use cases: Web integration; data collection; testing and verification

Essential reading

• What is RPA? A revolution in business process automation
• How to choose RPA software: 10 key factors to consider
• Understanding the process automation landscape
• 15 top RPA certifications
• 7 mistakes to avoid when developing RPAs
• Why RPA implementations fail