Table of Contents
Robotic Process Automation (RPA) tools are designed to mimic user behavior within a software system, via the use of software robots (bots), to automate high-frequency, deterministic business processes. Originally viewed as a tactical or narrowly focused solution, RPA tools have expanded to include features such as intelligent document processing (IDP), process discovery, and the incorporation of machine learning (ML). At the same time, they have become part of a broader automation landscape that includes business process management systems (BPMS), integration platforms, and artificial intelligence (AI).
The business context and strategy for RPA are equally as important as its technology features, if not more so. It’s easy to use the tools tactically to “paper over” cracks in processes that require proper analysis and change while applying RPA more broadly without due consideration will simply produce another tangled layer of point-to-point interfaces. Therefore, organizations should take a more strategic approach to their automation initiatives and use RPA alongside other tools, accompanied by suitable process analysis and change management.
From a market perspective, RPA is a highly active domain that has yet to reach maturity, with a large number of credible participants. The pioneers of RPA have grown to be sizable businesses, and are now being challenged by the major platform vendors, many of whom have entered the market through acquisitions. At the same time, there are a number of smaller innovators and specialists in particular applications of RPA, all challenging the market leaders.
In the accompanying GigaOm report “Key Criteria for Evaluating Robotic Process Automation (RPA) Tools,” we list the major features and evaluation metrics that should be applied when selecting an RPA solution. In this report, we analyze the leading solutions in the market, weigh the key criteria and evaluation metrics used to assess them, and identify important technologies to consider for the future. All vendors featured in this report offer viable solutions that are capable of providing core RPA features, but there is much greater differentiation in the more advanced areas that form the key criteria for evaluation. The report is intended to appeal to organizations looking to extend investments in existing platforms, as well as those starting out on their RPA journey.
How to Read this Report
This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding consider reviewing the following reports:
Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.
GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.
Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.
2. Market Categories
For a better understanding of the market and vendor positioning (Table 1), we assess how well solutions for RPA are positioned to serve specific market segments.
- Small-to-medium business (SMB): In this category, we assess solutions on their ability to meet the needs of organizations ranging from small businesses to medium-sized companies. Also assessed are departmental use cases in large enterprises, where ease of use and deployment are more important than extensive management functionality, data mobility, and feature set.
- Large enterprise: Here offerings are assessed on their ability to support large and business-critical projects. Optimal solutions in this category will have a strong focus on flexibility, performance, data services, and features to improve security and data protection. Scalability is another big differentiator, as is the ability to deploy the same service in different environments.
Table 1. Vendor Positioning
|Exceptional: Outstanding focus and execution
|Capable: Good but with room for improvement
|Limited: Lacking in execution and use cases
|Not applicable or absent
3. Key Criteria Comparison
Building on the findings from the GigaOm report “Key Criteria for Evaluating Robotic Process Automation (RPA) Tools,” Table 2 summarizes how each vendor included in this research performs in the areas that we consider differentiating and critical in this sector. Table 3 follows this with insight into each offering’s evaluation metrics—the top-line characteristics that define the impact each will have on an organization. The objective is to give the reader a snapshot of the technical capabilities of different solutions and define the perimeter of the market landscape.
Table 2. Key Criteria Comparison
|Intelligent Document Processing
|Process Discovery & Task Mining
|Exceptional: Outstanding focus and execution
|Capable: Good but with room for improvement
|Limited: Lacking in execution and use cases
|Not applicable or absent
Table 3. Evaluation Metrics Comparison
|Security & Compliance
|Licensing and Support
|Exceptional: Outstanding focus and execution
|Capable: Good but with room for improvement
|Limited: Lacking in execution and use cases
|Not applicable or absent
By combining the information provided in the tables above, the reader can develop a clear understanding of the technical solutions available in the market.
4. GigaOm Radar
This report synthesizes the analysis of key criteria and their impact on evaluation metrics to inform the GigaOm Radar graphic in Figure 1. The resulting chart is a forward-looking perspective on all the vendors in this report, based on their products’ technical capabilities and feature sets.
Figure 1. GigaOm Radar for Robotic Process Automation
The GigaOm Radar plots vendor solutions across a series of concentric rings, with those set closer to the center judged to be of higher overall value. The chart characterizes each vendor on two axes—Maturity versus Innovation, and Feature Play versus Platform Play—while providing an arrow that projects each solution’s evolution over the coming 12 to 18 months.
The Radar chart in Figure 1, portrays a highly dynamic market in which maturity is increasing, but innovation is still important. The early days of the RPA market were characterized by specialists, the foremost of which have now grown their capabilities into well-rounded and fully-featured solutions. These vendors currently sit in market-leading positions but are being challenged increasingly by major software vendors, most of whom have acquired RPA capabilities and are incorporating them into their existing automation platforms.
The cluster of vendors in the Mature/Platform Play quadrant of the radar indicates how core RPA is being augmented now by a wider set of capabilities, such as IDP, process discovery, and machine learning, and becoming part of a broader end-to-end automation story. However, the detail of core RPA still matters, and this has enabled the early market pioneers such as UIPath, Automation Anywhere, and Blue Prism to remain just ahead of the pack. Close behind are the major platform vendors, including Microsoft, IBM, and Salesforce (which has acquired Servicetrace), together with automation-focused vendors such as Pegasystems, EdgeVerve Systems, and WorkFusion. All vendors in this group are actively challenging the market leaders.
The RPA market is still in the early-to-mid stage of consolidation, and the Innovation/ Feature Play quadrant of the radar includes a number of specialists, including Jiffy.ai, Nintex, and Appian, who are either developing broader capabilities or have strengths in a particular aspect of RPA. Rounding out the Radar are NICE Systems in the Maturity/Feature Play quadrant, which has a strong focus on RPA in the contact center, and in the Innovation/Platform Play quadrant, SAP and Kryon, both of which are increasing the maturity of their respective broad-based solutions.
RPA is one piece of a broader automation ecosystem and overlaps or combines with a range of technologies such as BPMS, integration platforms, service management, and AI/ML. In some scenarios, RPA can be a tactical project, in which a smaller or more-focused vendor may be a better fit for the business requirement. In other cases, the goal may be broad-ranging automation, for which a more comprehensive platform comes into its own. All of the vendors featured in this report have satisfactory capabilities for core RPA, and we encourage clients to read the more detailed profiles of each vendor in the following section to get a fuller picture of their strengths and challenges.
Inside the GigaOm Radar
The GigaOm Radar weighs each vendor’s execution, roadmap, and ability to innovate to plot solutions along two axes, each set as opposing pairs. On the Y axis, Maturity recognizes solution stability, strength of ecosystem, and a conservative stance, while Innovation highlights technical innovation and a more aggressive approach. On the X axis, Feature Play connotes a narrow focus on niche or cutting-edge functionality, while Platform Play displays a broader platform focus and commitment to a comprehensive feature set.
The closer to center a solution sits, the better its execution and value, with top performers occupying the inner Leaders circle. The centermost circle is almost always empty, reserved for highly mature and consolidated markets that lack space for further innovation.
The GigaOm Radar offers a forward-looking assessment, plotting the current and projected position of each solution over a 12- to 18-month window. Arrows indicate travel based on strategy and pace of innovation, with vendors designated as Forward Movers, Fast Movers, or Outperformers based on their rate of progression.
Note that the Radar excludes vendor market share as a metric. The focus is on forward-looking analysis that emphasizes the value of innovation and differentiation over incumbent market position.
5. Vendor Insights
Appian Robotic Process Automation
Appian provides a low-code platform, with RPA forming an important addition to its overall offering, which also includes workflow, AI, broader low-code development, and API integration.
Features include a workflow designer that designs and builds bots in a visual environment, which uses low-code development and includes pre-built components. Appian is served by a developer community that has provided more than 625 components and extensions, which are available from the Appian AppMarket.
The solution uses an orchestration server to retrieve the required Java artifacts when an automated process is initiated, and assigns the bot to a resource. Appian-managed bots can run on local devices using a lightweight Appian agent, which communicates back to the server to get the next command. Appian supports both attended and unattended bots.
A single interface is provided for users, which is intuitive and accessible and combines data from many sources into a single view. Real-time analytics allows all bots and automated processes to be monitored through dashboards.
Appian IDP uses ML and OCR to extract information, with continuous training that is able to identify key values. The solution ships with pre-trained ML models that can be used by non-technical users to process documents, which promotes ease of use. Support is provided for Google ML as a third-party service, as an alternative to Appian’s native capability, which can be hosted in a container in Appian’s hosted cloud. All Google customers are single-tenant, and data that is processed using Google’s ML service is not used to train Google’s engine. An AI recommendation engine is also provided.
Appian provides hundreds of pre-built integrations, but they can also be created using the included API integration designer, which provides a no-code mechanism for integrating with applications. UI-based integrations are supported as well, using no-code/low-code development.
Appian RPA is cloud-native and is offered as part of Appian’s managed cloud on AWS. It dynamically scales, based on workloads. Built-in security is provided, including immutable audit trail logs, the ability to stop processes, and strong access rights and permissions. There are four levels of pricing. Community Edition is available for free, which enables companies to create limited production apps and unlimited bots. Application Edition is targeted at a department or specific use case, Platforms Edition is tuned for enterprise-wide deployments, and Unlimited Edition allows unlimited development.
Strengths: Appian’s focus is on building on its wider low-code development platform for large enterprise customers. The addition of RPA capabilities makes it attractive to existing Appian customers, as well as to enterprises that value the combined and integrated low-code options Appian provides.
Challenges: Appian’s enterprise focus and broad platform approach may not appeal to small-and-medium-sized enterprises seeking a focused RPA solution. Bot resilience capabilities are limited. Appian has acquired capabilities this year to enable a full end-to-end automation solution, but some users may find they need to license additional services, like Google ML, which can impact TCO.
Automation Anywhere Automation 360
Automation Anywhere (AA) is one of the big three market leaders in the RPA space. Key solution components are AARI, Discovery Bot, IQ Bot, RPA Workspace, and Bot Insight. Its latest solution, Automation 360, is a cloud-native RPA platform.
AARI is a low-code platform meant for business users to create bots. A library of common components is provided, and there is also a bot store that offers more than 1,200 products. A wide range of UI integrations is available, with AI used to add intelligence to the process for key applications. Many API-based integrations are also available, although some user feedback suggests they may be difficult to use.
Automation Anywhere Discovery Bot records human interactions for repeated processes, including variations. Bot blueprints are generated, which can then be used to create bots automatically. Also included is a universal recorder.
There is an easy-to-use analytics dashboard, and Bot Insight provides advanced analytics. Features include real-time health and performance monitoring, visual dashboards with actionable data about bots, and line of sight to ensure that SLAs are met. Native connectors and APIs provide integration with analytics tools such as Microsoft Power BI and Tableau, to enable data manipulation.
The web-based Control Room is the management console. In terms of orchestration, RPA Workspace provides both the development environment and the orchestration engine. Both attended and unattended bots are supported, and AA acquired KlevOps to support attended automation more effectively.
IQ Bot powers intelligent document processing, using AI technologies such as computer vision, NLP, fuzzy logic, and ML to classify, extract and validate information automatically from business documents and emails.
Automation Anywhere is a cloud-native RPA platform that uses microservices and container architecture, and it can be deployed to all the leading public cloud platforms. AA has a strong reputation for scalability that is backed up by a portfolio of large enterprise clients. It can also scale up from smaller deployments. Security and compliance features include real application clusters (RAC), end-to-end encryption, and SAML+Kerberos integrations. There is fixed pricing for bundled solutions, which is well suited to new customers, and an entry-level solution is available for the SMB market. Typical deployments are achieved within three to six months and a relatively quick ROI is possible.
Strengths: AA’s Automation 360 has a multi-role, easy-to-use UI that is especially useful for its SMB customers. Another particularly strong area is IDP, which is powered by IQ Bot and is attractive for processing large volumes of documents. It is also the only cloud-native RPA product available in the market.
Challenges: While AA has a good level of functionality across every area, and does not have any apparent weaknesses, there are areas where it could improve its capabilities. These include process discovery and task mining and AI.
Blue Prism Intelligent Automation Platform
Intelligent Automation Platform includes process discovery (Process Intelligence, Process Assessment, and Decipher IDP), bot design (Design Studio, Wireframe, and Capture), and execution (Blue Prism Cloud, Automation Lifecycle Management). Blue Prism Cloud is based on Azure.
Design Studio uses drag-and-drop techniques for building automation scripts. There is a large library of pre-built components and a marketplace for the sale of bots called Blue Prism Digital Exchange. Friendly, low-code development tools are provided.
The Control Room is the UI for assigning processes to bots. It includes the ability to scale task assignments and digital worker volume on-demand and provides real-time transparency of process performance. Dashboards provide insights into the health of the digital workforce, and it is easy to use for both developers and business users. Automated mining tools allow users to discover processes and capture integrations from digital process definition documents, and these can be opened in the Design Studio. Using the Automation Lifecycle Management (ALM) stack, processes can be imported from Capture into the ALM Process Definition.
Decipher IDP is Blue Prism’s tool for validating and extracting data from structured, unstructured, and semi-structured documents. OCR is included to extract text and text layout information from images, and an optional NLP plug-in is available. However, some users mention that there are limitations to the OCR capability.
Process Intelligence provides end-to-end process and task mining capabilities. Capture, which is Blue Prism’s process assessment tool, deploys AI and computer vision techniques. Capture can recognize and interpret screenshots, videos, and data gathered during process mapping. This information is then consolidated to be checked and rearranged, if required, by an analyst and exported in MS-Word or other software formats.
Blue Prism provides connectors to many enterprise applications, but it was later than many of its competitors in providing API integration. It also provides UI-based integration.
Blue Prism offers both on-premise and cloud-based deployment, with its SaaS offering based on Azure. Blue Prism has recently announced a strategic partnership with AWS and has added a range of on-demand SaaS options. It has proven scalability for enterprise deployments. It is rated as strong on security and compliance with enterprise-level security features. In terms of licensing, all-in or consumption-based pricing models are available, but it is often considered to be relatively expensive.
Strengths: Blue Prism’s marketplace, Blue Prism Digital Exchange, is a particular strength of the company and it has good capabilities across all key criteria areas. A differentiator is that it offers industry-specific solutions and accelerators. It also has one of the most scaled task automation tools.
Challenges: Blue Prism has addressed most weaknesses by releasing functionality during 2021. Where it may seek to improve is in its UX design vs its peers. It also does not offer a headless bot capability.
EdgeVerve Systems AssistEdge
EdgeVerve Systems Limited is a wholly-owned subsidiary of Infosys. Its portfolio includes AI (XtractEdge), automation (AssistEdge), and supply chain (TradeEdge). AssistEdge, its RPA product, is a unified automation platform that includes process automation, process discovery, and native AI capabilities. Other products in the AssistEdge portfolio include AssistEdge Design Studio, AssistEdge Discover, AssistEdge Engage, and AssistEdge Cloud.
AssistEdge Design Studio uses drag-and-drop capabilities, a low-code development platform to create workflows, and a library of pre-built components. There is also a marketplace with a range of paid and free bots. EdgeVerve lacks a full-scale web development tool, and customer feedback suggests that the UI is not as friendly as it could be for non-technical users.
A desktop recording tool is provided as part of AssistEdge Discover, which also includes the STARC AI engine. STARC analyzes the captured data to create actionable process insights, which are delivered through interactive maps, business dashboards, and automation blueprints.
There is a wide range of UI integrations provided, with AI used to add intelligence to the process for key applications. API integration is provided as well, via pre-built integrations with Infosys Nia, Google, Microsoft’s cognitive APIs, and SAP.
Both attended and unattended bots are supported, with the ability to transition seamlessly between attended and unattended automation.
IDP is supported through XtractEdge, which enables document extraction, processing, and comprehension. Deploying AI and ML, it ingests and extracts document layouts, text, and visual objects. It also enhances the extracted data with contextual information, analyzes the extracted data to derive insights, and makes the analyzed information available via downstream integration and search. Automated classification is supported, and data extraction from various document types and formats is possible without prior template training. A GUI workbench is provided for guided manual review and a performance analytics dashboard is available.
Bot resilience is enabled through a service called Albie, a cognitive engine that helps resolve and reduce errors. There is also error and exception handling.
Deployment options are either cloud or on-premises. AssistEdge is GDPR ready, SAML and OIDC compliant, and integrated with Cyberark. Flexible pricing models are available, including pay per use, automation as a service, and gain-sharing/outcome-driven models.
Strengths: EdgeVerve has good capabilities across most areas of its offering. Its AI capabilities, which are embedded throughout the platform, provide a strength encompassing more than 40 patents. It also has extensive IDP capabilities, which will appeal to customers in its target markets.
Challenges: The product is sold only via the Infosys sales and channel partner network. Moreover, the process discovery and task mining capabilities can be used only with EdgeVerve RPA, as it is not a standalone product.
IBM Robotic Process Automation
IBM’s robotic process automation solution provides RPA, Intelligent Automation (IA), Interactive Voice Response (IVR), and chatbots. It is part of IBM Cloud Pak for Automation, a set of integrated solutions including AI-generated recommendations, analytics, and low-code tooling.
IBM Robotic Process Automation Studio is used to develop, run, test, and publish bots, using a low-code development approach and hundreds of pre-built commands. A module is included to create flowcharts using the Business Process Management Notation (BPMN) format.
The IBM RPA Studio recorder uses a low-code approach to record user interactions and can be used to generate bot scripts automatically.
The analytics capability provides dashboard reports with a number of pre-built reports including Data Source Jobs, Data Source Counters, Workflows, and Processes. A variety of charts and indicators are available.
IDP is supported through built-in OCR to extract structured data from unstructured content. RPA commands can be captured out-of-the-box for data extraction and classification. This is an area where the wider capabilities of IBM Cloud Pak for Business Automation are required for advanced use cases. To achieve the full benefit of IBM’s capabilities, the cloud-native solution, Automation Document Processing, provides a set of AI-powered services that read and correct data from documents automatically, using a no-code interface for training models on document classification, data extraction, and data enrichments.
IBM Cloud Pak for Business Automation provides the ability to discover process flows by applying data mining algorithms to event logs, including extracting data from enterprise applications such as SAP, Salesforce, Workday, and IBM Rational, and then automatically generating process models. Combining this with task mining provides a detailed picture of a process.
IBM has AI-powered RPA features that include integrated chatbots, with the ability to create intelligent virtual agents that can be deployed on multiple channels to provide engaging client interactions. Native AI features include ML, decisioning, and fuzzy logic, which are available through a drag-and-drop interface. AI is also leveraged for intelligent workload management that distributes workloads across multiple bots to optimize throughput.
Attended and unattended bots are supported, and unattended bots can be scheduled. Deployment options are cloud, with a SaaS-based model, or on-premises. Work is distributed intelligently across multiple bots, and scalability can be increased by running multiple bots on the same virtual host. A no-cost 30-day trial of the solution is available and includes the capabilities required to build bots, intelligent virtual agents, and dashboards. SaaS or on-premises starter packs are available for a monthly fee.
Strengths: IBM’s AI capabilities are particularly strong. However, these enhanced capabilities are provided when IBM RPA is combined with IBM Cloud Pak for Business Automation, making it likely best suited to existing customers of that product who want to add RPA.
Challenges: The biggest challenge for IBM is the lack of a bot store or marketplace. Having acquired an RPA vendor, WDG Automation, to boost its automation capabilities, IBM now needs to extend and enhance those capabilities.
Automation scripts are built using Jiffy.ai’s Automation Studio, which provides a low-code application-based solution, using drag-and-drop capabilities. This solution works with configurable HyperApps for specific verticals, which are low-code applications that can be designed and deployed quickly. It provides pre-built components but customer feedback for this feature suggests it’s not great. Although Jiffy.ai does not have a marketplace where developers and enterprises can contribute or buy bots, it does offer HyperApps for horizontal and industry-specific use cases.
The Core JIFFY.ai engine enables automation across different applications. The execution engine provides a scheduling capability, and users can assign Bot Clusters within the JIFFY.ai core to execute the task. Each block of steps within a task can be picked up by any of the bots in a bot cluster, flexibility that provides scalability and resilience in the case of bot failures.
JIFFY.ai Automate has a hybrid document processing engine for IDP, with self-learning ML models that can handle complex and diverse document types, eliminating the need to build ML models from scratch. A built-in deep learning OCR engine integrates seamlessly with third-party OCR solutions.
A recording capability that allows users to record the UI elements of applications to be automated is also included, and the UILearn module is used for this purpose. AI, ML, NLP, Analytics, and cognitive automation capabilities with human-in-the-loop are all built into the platform. The cognitive server enables bot self-learning using dynamically captured data, and technologies such as NLP, image processing, pattern recognition, and contextual analysis. The Analytics engine handles data visualization and processing.
Both attended and unattended bots are supported. In terms of the resilience of its bots, the solution includes capabilities for exception handling. However, it does not have an end-to-end automation suite.
Deployment is via a unified cloud-native platform, which can be deployed to public, private, or hybrid environments. In terms of security and compliance, Jiffy.ai offers good execution-level security. It uses a volume-based subscription model, which is considered in the marketplace to be competitive, but as a relative newcomer to the market, its support is considered immature.
Strengths: Jiffy.ai is strong across many areas including its UI, IDP, and AI capabilities. Automation Studio, analytics, orchestration capabilities, and its universal recorder also offer good levels of functionality.
Challenges: As a relative newcomer to the RPA market, Jiffy is missing a number of advanced capabilities, including process discovery and task mining. It has fewer pre-built components than competitors do and limited API-based integration capabilities. The lack of a marketplace is also a challenge.
Kryon Systems provides full-cycle automation, which comprises discovery, RPA, and analytics.
Kryon’s automated discovery capability captures repeated processes on desktops using computer vision to take screenshots, and all mouse and key clicks are recorded, as are applications and tools accessed during the process. AI is used to identify processes by looking for repeated patterns of behavior, such as common steps. Variations and exceptions are also recorded.
Captured processes are displayed via a dashboard. Users can drill down to view processes graphically and are able to click on each activity to see all of the key clicks and the screens that were displayed at each stage. There is also a playback facility that allows users to see how different users operate the same process.
These processes can be imported directly into RPA Studio for developers to turn into automated processes. Alternatively, the developer can run through and record the process, which can be presented in a Word document. More than 200 OOTB advanced commands are included.
IDP is supported through cognitive capabilities and OCR, using a best-of-breed approach, which allows all use cases to be supported with structured and unstructured document and text analysis. Integrations with ABBYY and Microsoft Cognitive Services are provided.
Kryon Console provides an intuitive UI, from which users can see the tasks that are being run by each bot, the current status, and any failures. Triggers can be set to determine when unattended bots should run, which could be time-based, email directed, or created to kick in when files change.
Kryon incorporates OOTB reporting for attended and unattended RPA and process discovery through a customizable report generator. Real-time and historical data reporting via the Kryon ConsoleX dashboard is also available.
Kryon offers flexible deployment options comprising on-premises, hybrid, and SaaS. It is highly scalable, supporting 100,000 robots, including support for a robot fleet that enables organizations to scale robots dynamically over AWS workloads according to the organization’s needs. Security measures include adherence to the latest security standards as well as data protection measures. These include saving all data in the customer’s on-premises or private cloud environment, rather than on Kryon servers, and using strong encryption both at rest and in transit. Any PII from screens collected during robot runtime is deleted immediately and information contained in screenshots can be masked permanently.
Strengths: Kyron has good capabilities across most areas, including IDP, process discovery, and task mining, and good AI/ML capabilities. A particular strength is its automated process discovery capabilities that include the ability to record process interactions, which makes it an attractive proposition.
Challenges: The process discovery capability is limited to Kryon RPA only because this is not a standalone product that can be used with other RPA platforms. Additionally, API-based integration is weak as it is not a focus for the vendor.
Microsoft Power Automate
Power Automate, Microsoft’s RPA solution, is part of Microsoft Power Platform, and there is seamless integration with other elements of the Power Platform, including Power BI, Power Apps, and Power Virtual Agents. Power Automate is built into Windows 11 and available for free, allowing users to automate manual tasks from the Windows desktop. Power Automate also includes process and task mining capabilities through its Process Advisor feature.
Power Automate is most efficient when it is combined with all of the components of Microsoft Power Platform, which is required to create a single, unified, end-to-end platform that offers automation, integration, low-code application development, and analytics capabilities to address business process automation requirements.
A built-in recorder allows processes to be captured with the option to remove sensitive information from the recording. Built-in analytics and process mining capabilities show visualizations of end-to-end processes, and guided recommendations are provided to help optimize workflows.
Process Advisor makes processes visible, allowing users to analyze how efficiently processes are running, providing an understanding of usage patterns to optimize capacity, and giving an overview of daily, weekly, and monthly desktop flow run statistics, including which flows are being used most.
Power Platform Admin Center provides a central point from which to manage an organization’s data policies and environments. Administrators are able to create rules that manage the ways business data is shared among services in flows.
In order to build IDP solutions, components from Microsoft Power Platform are required. Power Automate is used to orchestrate the overall process, and AI Builder provides the AI and ML capabilities necessary to extract information from documents. Power Apps allows users to review and approve documents manually, and Dataverse manages the document queue and stores all the data, files, and configurations required.
A community marketplace where partners and developers can create bots is available. Power Automate is cloud-only, running in Microsoft Azure.
Strengths: Microsoft is strong across most areas, with a UI that’s considered to be intuitive and easy to use for business users and developers, and its powerful AI and ML capabilities available via Azure enhance its capabilities. Power Automate works best when used with Microsoft Power Platform. It also provides attractive pricing for organizations of all sizes.
Challenges: Microsoft suffers from the lack of a bot marketplace, although there are a large number of applications, components, and connectors available from Microsoft’s website. However, most of these have been developed by Microsoft partners, rather than by the vendor itself.
NICE Systems NICE Robotic Process Automation
NICE’s approach to RPA is to include everything needed for RPA in a single solution: NICE Robotic Process Automation. The solution includes NEVA, a virtual desktop automation assistant, which uses AI to recommend automations and next-best actions.
NICE has a particular focus on contact-center automation and offers a number of pre-built solutions for contact-center applications across different industries. Customers are mainly large enterprises.
The design tool, Automation Studio, provides drag-and-drop functionality with pre-built components, and support for both attended and unattended bot development. It includes a native debugger and in-built automatic testing.
NICE Automation Finder is an automation discovery tool, which is AI-infused. Besides recording and collecting information to identify desktop tasks undertaken by employees, it also detects variations. These are used to recommend the best candidates for automation, which are presented in a report. These processes can then be developed automatically via the click-to-automate feature in Automation Studio. Automation Finder uses NICE’s Desktop Analytics and unsupervised ML algorithms. However, there are no process-mining capabilities.
A good range of analytics is provided, including capturing data, generating insights about employee behavior on the desktop, productivity scores, and knowledge gaps, and identifying inefficient processes through NICE Desktop Analytics. NICE also provides speech analytics, delivering insights into customer interactions. AI is used throughout the solution, including in its voice analytics and next-best-offer recommendations.
NICE supports both attended and unattended bots, although it is stronger in the attended bot space, which reflects its contact-center automation focus. There is no native capability for IDP, although third-party services can be connected.
A large number of API-based integrations are available, and there is a bot marketplace. However, a potential area of weakness is that it is difficult to analyze bot failures.
The focus on the contact center may make the solution less suitable for other application areas. NICE RPA has a cloud-native architecture with microservices and containers, and it can be deployed in public or private cloud environments. Its elastic cloud architecture enables infrastructure scalability, and in the area of security and compliance, it has strong controls for regulated industries. It has all-inclusive pricing, which is considered to be relatively low in the marketplace. In the contact center space in particular, NICE is recognized as delivering strong value to customers.
Strengths: NICE has good capabilities across most areas. Its strength in voice analytics and focus on attended bots make it attractive to enterprises for whom managing contact centers is a key part of their business.
Challenges: NICE faces challenges, including limited capabilities in the universal recorder area, and in IDP, which requires third-party tools. NICE’s focus on contact centers, with pre-built solutions for contact-center applications across different industries, makes it something of a niche product.
Nintex provides process management and automation software for managing, automating, and optimizing business processes and workflows. The acquisition of K2 in 2020 enhanced its forms and mobile capabilities, adding support for more advanced workflows and orchestration, and enhancing its capabilities in other areas of its platform.
Nintex RPA has been designed to be easy to use. A visual design environment is provided to build automation scripts using drag-and-drop design tools that are accessible by non-technical users.
Although there is no universal recording capability, there are limited facilities for recording mouse clicks using the Record Mouse tool. This tool can record a sequence of mouse clicks as actions, which can then be added to a workflow. However, the solution does have more than 300 actions, process maps, and pre-built workflow templates to help get automated processes up and running quickly. It also has direct API connectivity to applications to help speed up bot development through the Nintex Workflow Cloud API. Out-of-the-box connectors include SharePoint Online, OneDrive, Dynamics CRM, Salesforce, Dropbox, Twilio, Slack, Google Drive, Azure AD, SQL, and more.
Due to its easy bot building capabilities, Nintex RPA is well suited to one-off, operationally focused scenarios in which attended and unattended bots need to be built quickly to address a specific requirement, or to be incorporated into a broader workflow.
Business process analytics tools for gaining insights into the efficiency and performance of processes are provided and have the ability to identify bottlenecks.
Nintex RPA Central provides control and orchestration of bots through a web interface, and enterprise-grade encryption is included.
Nintex does not support IDP currently, in terms of extracting data from documents, but it does have an intelligent PDF form converter. This tool takes PDF forms and turns them into digital renditions, which can be utilized in a workflow to capture and display information related to the process. AI and ML capabilities are provided currently through integration with third-party products only, although this is an area where Nintex is looking to develop its own capabilities.
Nintex Gateway is a feature that serves customers looking for end-to-end automation, rather than pure-play RPA. It provides bi-directional, seamless communications between Nintex Workflow Cloud and Nintex RPA, with the ability to drag-and-drop components between the two.
Pricing is on a per-project basis, regardless of the number of bots being deployed, which makes it very easy to scale up the number of bots being used. Nintex Workflow customers also have access to Nintex RPA as part of their Enterprise license.
Strengths: Strong areas for Nintex include its UI, API-based integration, and bot resilience. It is best suited to use cases for which bots need to be built to solve a specific requirement, or as part of an end-to-end workflow.
Challenges: The lack of IDP capabilities is a challenge for Nintex, as it’s often requested by customers. Adding IDP to the portfolio is on the Nintex roadmap, as is process mining, which is needed to improve process discovery.
Pegasystems: Pega Robotic Process Automation
Pega Robotic Process Automation comprises two solutions: Pega Robotic Automation provides the automation of manual and repetitive tasks, and Pega Robot Manager is the central application used to manage the configuration and work of attended and unattended bots. Enterprises looking for an end-to-end RPA automation suite would need to license both of these solutions.
Design Studio provides a rapid visual development environment, with the ability to apply business rules through shapes, or by recording workflows using the recording capability. Pega Robot Runtime provides the environment to run automations. Pega Robot Studio works within the Microsoft Visual Studio design environment using a plug-in that integrates with Visual Studio 2015. A standalone version of Robot Studio is available that installs the Microsoft Visual Studio 2015 Isolated Shell during the Robot Studio installation. Manual tasks can be recorded and exported in either Word or PDF format, including the steps, corresponding screenshots, and descriptions users can add to document the process. Sensitive data can be hidden by blurring the content.
Pega provides a low-code development platform, which is considered to be reasonably intuitive but with some degree of complexity involved. It also provides a library of pre-built components, offers micro journeys, which are reusable applications, and maintains a strong community with a marketplace for applications, components, and bots.
A management console allows users to orchestrate, manage, and prioritize the queuing of work and processing activity for Pega software robots. Dashboards, reports, and drill-downs that monitor robot health, work status, SLA compliance, and auditing are provided.
OCR is provided with the ability to extract text from pictures and highlight entities, along with out-of-the-box integration with email bot channels. The functionality is available to process flows, and it works with both structured documents and forms analysis. It is available on-premises, on the server, on the client, or on the cloud (multi-tenant).
Pega Workforce Intelligence uses AI for task mining, and X-Ray Vision helps identify potential automation. NLP and AI provide intelligent email processing, and chatbots and virtual assistants are included. In addition, pre-built AI/ML models for decision automation are provided.
The solution is available as a fully managed SaaS, a client-managed cloud, or on-premises.
Strengths: Pega is particularly strong in task mining and discovery, and in bot resilience capabilities through its X-ray Vision feature. Pega also has a strong community with a marketplace that enables enterprises to buy pre-built applications, components, and bots.
Challenges: Pega offers only OCR capabilities and not broader IDP features. It also requires more than one product to create an end-to-end solution, through Pega Robotic Automation and Pega Robot Manager. Combining both products into a single end-to-end solution would improve Pega’s proposition.
SAP Intelligent Robotic Process Automation
SAP’s RPA solution is SAP Intelligent Robotic Process Automation (iRPA). The acquisition of the BPM vendor Signavio in March 2021 boosted its end-to-end BPA capabilities. iRPA is very much focused on the SAP ecosystem and SAP use cases. Customers tend to be large enterprises.
There are two options for building automation scripts: Cloud Studio or Desktop Studio. A recording capability is included with the solution and has the ability to export recordings into Cloud Studio. While Cloud Studio is considered usable, less AI is built into its UI than some other RPA products have.
The cloud-based component, SAP Intelligent Robotic Process Automation Factory, provides the ability to configure and distribute process automation packages for attended and unattended bots. It works seamlessly with desktop agents deployed on-premises. It also allows the monitoring of agents, package deployment, and job execution.
Orchestration and monitoring process automation is undertaken using Cloud factory, which is a cloud-based solution powered by the SAP cloud platform. It does not require any additional deployment, and it manages environments, hierarchies, and script packages.
Process discovery and task mining are included, although they are currently seen as basic. Improvement in this area is on the roadmap through the acquisition of Signavio. AI, ML, and NLP capabilities are also weaker than competitor products, although SAP Conversational AI for NLP can be used.
Both UI and API-based integrations are available. API integration is provided through an API trigger and notifier using the underlying SAP BTP integration capabilities.
Both attended and unattended bots are supported, and while there are no auto-recovery capabilities for bots, there are good exception-handling facilities.
iRPA runs on SAP Business Technology Platform (BTP) as SaaS. The BTP platform ensures it is scalable and also provides strong security. A free trial is available and a consumption-based pricing model then follows. In terms of ROI and TCO, the solution is very dependent on the SAP ecosystem.
Strengths: SAP benefits from having a larger portfolio because there are several areas where additional SAP products are required to enhance the capabilities. These include IDP, for which SAP Business Document Processing can be deployed to provide a good level of capability.
Challenges: SAP’s solution is sold mainly in conjunction with SAP business applications rather than as a stand-alone product. It also has limitations in its IDP capabilities, which require an additional SAP product, and has only basic process discovery capabilities.
Servicetrace started developing software robots back in 2004. Its portfolio comprises RPA, test automation, and application performance monitoring. It was acquired by Salesforce in September 2021, and merged with the API platform provider MuleSoft to create an integration and automation platform. Its XceleratorOne (X1) solution is targeted at SMBs, large enterprises, government, and NGOs.
X1 Process Recorder records user actions in Windows applications, automatically creating both the click-path documentation and the process model in BPMN 2.0. Parts of the RPA workflow can be created automatically. Several recordings of the same process can be merged to allow different methods of executing the process to be included, as well as different decision branches. In addition, the recordings generate XES files that provide extensive data for connected process-mining tools. The X1 Process Recorder also supports and simplifies process mining, as the XES file generated by the recorder can be imported easily into process mining tools for analyzing processes and user behavior to optimize automated processes.
The integrated Business Process Management Engine provides the ability to model processes in BPMN 2.0 in the design phase of the automation. X1 Design Studio is a toolbox for RPA development, allowing workflows to be designed using drag-and-drop and low-code capabilities, thus enabling business users to build bots without the need to write code.
X1’s intuitive interface means that non-technical users can perform many tasks within the system. Both UI- and API-based integrations are provided, and attended and unattended bots are supported.
The OCR capability uses AI, which offers intelligent text and character recognition, allowing content to be recognized even in poor renderings. Servicetrace’s patented image-recognition OCR technology is based on human vision. It works by reducing an image or pattern to just the features that are required for recognition and hiding those that are not important, via the application of intelligent “fuzzy logic,” which has the benefit of producing fewer errors and malfunctions. With one image search, it handles up to 50 varying images in parallel. It also reacts to exceptions and heals itself partially through special configuration and variant handling.
Servicetrace offers a choice of deployment models—cloud, SaaS, web-based, Windows (on-premises), and desktop (on-premises). X1 Scaling allows several RPA sessions to run in parallel. The integrated scaling technology has multiple patents. Configuring additional RPA capacity can be achieved through a few clicks. Security and compliance management is included in X1 with a number of features, including X1 Secure Sessions, which run as invisible desktop sessions. Pricing is on a per-feature basis.
Strengths: Servicetrace is strong across most areas of functionality, but it is particularly strong in its API-based integration capabilities, in which it benefits from its merger with MuleSoft. Another advantage is the ability to create headless bots, which very few of its competitors are able to do.
Challenges: While Servicetrace provides some pre-built bots for application performance management and software testing, it does not offer an extensive list, and this is a limitation of the solution.
UiPath is the leading RPA vendor with more than 9,000 customers. It primarily targets large enterprises, although approximately a third of its customer base comprises SMB and mid-market organizations for which it has a separate go-to-market strategy and a free Community Edition of its platform. It is also the most well-developed RPA system available in the marketplace.
UiPath’s Studio family of products provides a common foundation for users with different levels of skills to build their own automations. StudioX is designed for business users and is no-code; Studio requires RPA developer programming knowledge, and Studio Pro needs the advanced programming skills of an RPA developer. Studio provides a low code, visual design environment, with more than 800 available out-of-the-box activities and thousands more available via the UiPath Marketplace. All bots contributed to the marketplace are curated and validated by UiPath.
In addition to UI integration, UiPath also provides more than 200 pre-built API connectors to common enterprise systems, enabling users to drag and drop integrations into automation workflows.
A recorder allows the recording of processes, with the ability to take screenshots and export process definition documents as editable, build-ready automation “blueprints.”
Pre-built templates are provided, as are dashboards for measuring automation performance and business impact. Centralized operations management for automation projects is also provided, with the ability to set access, automation, and review policies.
IDP is supported using either UiPath’s native OCR engine or a third-party engine. It can handle a wide range of elements, including tables, images, checkboxes, handwriting, and signatures. Pre-built retrainable ML modules for common document types are available in multiple languages.
Process-mining capabilities allow event logs to be analyzed to gain an understanding of the ways work is undertaken and to identify high-value automation opportunities. Root cause analysis can be deployed to understand deviations from processes. Employees’ day-to-day desktop activities can be captured and analyzed using AI for repetitive tasks that are ideal for automation. Process definition documents can be exported as editable, build-ready automation blueprints for RPA developers.
AI capabilities include more than 25 ML models for language analysis, translation, image analysis, document processing, time series, and tabular data, which can be dragged and dropped into automation workflows. AI-powered chatbots are also supported.
Robot resilience is built into the platform with auto-updating of robots and the desktop client, as well as robot self-healing.
Both cloud and on-premise deployment models are available. In terms of scalability, UiPath has enterprise customers that have deployed upward of thirty thousand attended and unattended bots.
Strengths: UiPath is the leading RPA vendor because it has the most comprehensive offering. It is notably strong in its UI, process discovery and task mining, API-based integration, and its bot store. Its platform offers a highly flexible and scalable solution with impressive security and compliance features.
Challenges: Although the product does not have any weak areas, there is always room for improvement. UiPath arguably could improve its IDP capabilities, bot resilience, and AI capabilities.
WorkFusion Intelligent Automation Cloud
WorkFusion Intelligent Automation Cloud offers discovery tools including Use Case Navigator, which allows users to evaluate use cases using their own data, and pre-trained bots provided by WorkFusion. However, the use cases are task and industry-specific. A recording facility is available.
Workflow design is enabled through Automation Studio, using cloud and desktop tools that also allow bot training. Applications can be automated without the need for coding, with pre-packaged components and an IDE for advanced cases available. Pre-packaged bots are available, but these are mostly industry-specific, and while there are some API integration capabilities, again these tend to be specific to industry sector use cases.
Embedded analytics provide business users with an overview of business and technical KPIs across processes, bots, and people.
IDP is supported through out-of-the-box AI bots, which are pre-trained on industry-specific documents that require no coding or developer skills. Network learning and model re-training by business users via human-in-the-loop ensure continuous learning. IDP features include digitization, data cleaning and analysis, as well as data extraction, classification, and matching.
Orchestration capabilities allow the management of end-to-end automation workflows, with an overview of the collaborative work of multiple bots and human-in-the-loop functionality.
Deployment options are cloud or on-premise. In terms of scalability, the solution addresses high volume processing financial services. It provides enterprise-grade security to the standard required by banks and has several security certifications. The licensing model is based on the cost of the platform plus a cost per process. WorkFusion scores well on review sites for support. In terms of ROI and TCO, several case studies show significant savings and very strong ROI.
Strengths: The Workflow Designer is particularly strong when used for designing complex processes. AI, ML, and NLP are strengths of WorkFusion, with pre-trained ML models provided for specific use cases. It also has a leading IDP solution.
Challenges: WorkFusion does not offer process mining and focuses on an automation roadmap instead, which may not suit all customers. Ease of use for non-technical users is an area where the vendor rates poorly, with user feedback claiming that some programming knowledge is required.
6. Analyst’s Take
The solutions in this Radar report represent a range of strategies. The leaders in the space—like UiPath, Blue Prism, and Automation Anywhere—have built sophisticated platforms offering a breadth of features and ease of use. Other vendors have found that tuning their services to more specific needs, like certain sector requirements, call-center attended bots, or identifying the processes to automate, have brought them a strong client base. In other cases, solutions are valued that may only solve simpler use cases but do that very well.
This specialization approach does face direct challenges from the likes of Microsoft, IBM, and SAP, who are increasingly bundling RPA services with compelling licensing models, and pose fewer barriers to adoption for existing customers of their enterprise software. There is still plenty of room for innovation, though, even for the largest players, and we expect to see further market consolidation over the next year or two, which will round out vendor offerings.
Determining where RPA sits as a solution in both current and future architecture is key to selecting the right vendor. There are many manual processes that it would not make sense to build a full solution for, from an ROI perspective, but RPA can be extremely effective in reducing the number of low-value human interaction points. However, identifying and understanding the use cases an enterprise will attempt to automate with RPA, and which ones should be re-engineered, will define whether long-term efficiency is truly achieved. There are pitfalls where RPA turns into a replacement for investment in infrastructure, forward-thinking architecture, and the ability to respond dynamically to the needs of the business.
Arguably, given the current demand for developer talent, the capacity for enterprises to manage processes like migrating their functions to the cloud or deploying SaaS platforms in their stack may be limited and prone to risks of delay and overspending. Therefore, RPA may be the necessary and useful bridge between the point where a company sets its technology north star and the practicalities of solving IT problems in the short term.
For more information about our research process for Key Criteria and Radar reports, please visit our Methodology.
8. About Ben Stanford
Based in West London UK, Ben is a seasoned IT consultant and technical program manager who has worked with all scales of organization from early-stage technology startups to global enterprises. He was an Executive Director in Engineering at Goldman, delivering large scale software development programs and specializing in the assessment and implementation of SaaS vendor solutions. His career has given him a broad range of experience from Google-sponsored retail tech to media and fintech. Ben is also a passionate agile practitioner, coaching teams to excel at delivery.
9. About GigaOm
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