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Progress enters the cognitive software sector with DataRPM

Progress enters the cognitive software sector with DataRPM

By Nicolas Payette

Published: 25 April 2025

Progress has persevered and intends to remain present and innovative in the field of enterprise software development platforms in the face of powerful competitors such as IBM, Oracle, Microsoft, Salesforce, Amazon and SAP. Although its size and marketing clout remain fairly modest, Progress has nonetheless enjoyed success by offering free, affordable, standardised and relatively simple development tools to its partners and large customers.

Progress' new two-pronged strategy introduced in 2017

At the end of 2016, the vendor announced the arrival of a new CEO, Yogesh Gupta, who from the beginning of 2017 presented the company's new strategy, based on two axes. The first axis is to strengthen his company's core business, which consists mainly of the flagship OpenEdge software development platform, DataDirect Cloud Integration (DCI) software and other development tools (e.g. Telerik, Rollbase, etc.). The second is artificial intelligence.

1. The flagship OpenEdge software development platform

OpenEdge remains a powerful software development platform on which tens of thousands of organisations depend for their most critical operations. Progress partners such as QAD, Aptean and TOTVS continue to attract new customers for their ERP solutions built on OpenEdge, and their efforts are critical to Progress' long-term success. The upcoming release, OpenEdge 11.7, will feature several enhancements in the areas of security, high-performance replication and always-on functionality.

Another important recent update was the Telerik DevCraft suite for .NET developers, a comprehensive toolkit for desktop, web and mobile user interface (UI) development. This new release includes support for Angular, Visual Studio 2017, JQuery 3, ASP.NET core and Xamarin, as well as new tools for faster desktop UI development.

2. The shift to cognitive computing (Artificial Intelligence)

The second pillar of Progress' strategy is to provide a forward-looking software development platform for developers to create cognitive business applications. This is exactly what IBM has done with Watson, Salesforce with Einstein, Microsoft with Azure Cognitive Services, Amazon with ASW Cloud Cognitive Services, and so on.

Progress has many essential elements for a cognitive applications platform, including a platform for creating business applications, front-end tools and mobility (a native script for creating iOS and Android applications and for web user interface development tools), back-end services, business rules and data connectivity. However, its product catalogue lacks a key component: machine learning or predictive analysis.

To this end, Progress recently acquired DataRPM, a provider of predictive maintenance and machine learning services.

Acquisition of DataRPM for 30 million dollars

The acquired software start-up has around 40 employees, most of whom are located in Bangalore, India. The purchase price was around 30 million dollars.

DataRPM automates predictive modelling, leveraging proprietary meta-learning capabilities that enable companies such as Jaguar, Samsung, Mitsubishi Heavy Industries and Cisco to dramatically increase the quality and accuracy of hardware failure predictions. Its machine learning technologies give application development companies the ability to leverage big data for commercial advantage in the industrial Internet of Things (IoT) market.

Predictive maintenance

Clearly, the world of cognitive software is vast. To select the first cognitive application area to target, Progress analysed its OpenEdge ISV partner base. Nearly half of these partners have production ERP solutions, giving Progress a strong presence in the manufacturing and industrial sectors. This has led the supplier to choose predictive maintenance as the main field in which to focus the cognitive functionalities of its software development platform.

Progress estimates the value of the cognitive predictive maintenance market at nearly one billion dollars, with growth of more than 30% per year. Competition is fragmented, with no dominant player, and the target audience is commercial application developers, a group that Progress knows well and appreciates its credibility. DataRPM is also a scalable platform that can be deployed in a hybrid cloud environment (both public and private clouds), providing a robust offering in the predictive maintenance market and giving competitors such as Ramco Systems, IFS, SAP, IBM Maximo, etc. a run for their money.

Although the acquisition of Progress will enable the company to recover what was missing from its catalogue, it is still unclear how it will deal with Big Data storage or Data Lake requirements. DataRPM does have some powerful partners, such as Cloudera, who are experts in Big Data storage (particularly in the Data Lake), but they are weaker when it comes to analysis and modelling. Although on the face of it this seems like a good option, the difficulty lies in finding a Data Lake that is simple and relatively inexpensive to design and maintain, and that can be easily integrated with DataRPM.

It always takes time and effort to aggregate reliable megadata from different sources to get real value. Cloudera, HortonWorks and MapR are complex and have a high density of services. Although their data warehousing solutions (lakes) are based on open source, whatever they say, they need a group of data specialists to make their database/lake relevant and easy to maintain. MapR might be the easiest in some cases, because it has focused on some vertical solutions that are repeatable.

From here, it will be interesting to see if Progress makes another investment or opens up the DataRPM technical partner panel further to more members of the NoSQL database/Data Lake community. Progress has begun integrating DataRPM technology with OpenEdge and its other products, to enable its partners to have predictive analytics capabilities in their application. Progress is expected to complete this integration by the end of the year.

Growth prospects for cognitive software

DataRPM will remain an independent and flexible unit and the integration efforts mentioned above will not disrupt its team's ability to innovate on its platform or its propensity to seek out new customers. It will be interesting to see whether Progress will reposition DataRPM as a general-purpose machine learning or predictive analytics module, or whether it will prefer to turn it into a specific 'predictive maintenance' machine learning solution.

Initially, DataRPM was a horizontally hierarchical start-up specialising in machine learning, whose 'predictive maintenance' focus was only circumstantial, with the capture of new customers over the past year, including the high-profile ones mentioned above. The company's team carries out paid proofs of concept to demonstrate to customers that what they are being offered generates value. This is usually a 90-day proof of concept, which is then transformed into an annual subscription for a concrete use case. Watch this video for more information:

The aim is to extend the number of use cases over time (e.g. product and content recommendations, customer churn predictions, conversion predictions, etc.) so that it can charge more for its solutions. DataRPM has adopted an 'occupy and expand' strategy that is set to continue. Its machine learning capabilities will form the foundation of Progress' forthcoming Cognitive Application Platform (later this year), which will also benefit from the back-end services capabilities of the Progress Telerik platform, front-end UX support from Progress Telerik UI tools, and data connectivity from Progress DataDirect.

Conclusion

Progress seems to have made a good deal with this acquisition, and we will keep a keen eye on future developments. Progress Partners, potential customers and existing customers should talk to the vendor about its intentions for DataRPM and how the solution could be applied to use cases specific to their industries.

Article translated from French