When we say that the 2017 SAP SAPPHIRE NOW conference was all about the Italian Renaissance, of course we mean SAP Leonardo. SAP used the show to launch its “system of innovation” featuring various functions and competencies.

There’s no accident that SAP chose to name its product after Leonardo da Vinci. Signore da Vinci was known as a polymath (or person of many skills), due to his impressive talents that spanned painting, sculpture, architecture, astronomy, mathematics, engineering, and more.

SAP has used the time in between 2017 SAPPHIRE NOW and SAP TechEd Barcelona to roll out a series of updates, extensions, and enhancements to SAP Leonardo. It’s been working to clarify how SAP Leonardo can bring automation efficiencies, introduce best practices, deliver data effectiveness, and apply all-around application workflow excellence.

Getting Chatty with the Bots

Those of us who thought that SAP might spend more of its time talking about the back-end extensions happening in SAP Leonardo have had our eyes opened. Recent developments are still on the back end, but they’re manifesting themselves in front-end functionality.

The company has focused on finessing and upgrading the SAP Conversational AI service inside SAP Leonardo. This software component is designed to allow customers to build sophisticated corporate chatbots more easily. What is a “sophisticated” corporate chatbot? Well it’s not going to offer you pre-dinner aperitifs or cigars after your meal. SAP is suggesting that its software can understand the business models that customers run and can handle human conversations at a deeper level.

These conversations can support customers through a fully automated chatbot experience that knows the answers to their questions. There also are chatbot conversations that can serve internal staff requests for information—think of this as an automated helpdesk for IT or other departments.

Putting the I in RPA

The type of automation intelligence in SAP Leonardo runs in line with the firm’s work to invest in Robotic Process Automation (RPA). The difference is that SAP likes to call it Intelligent Robotic Process Automation (IRPA).

RPA essentially exists to automate repetitive business processes across a customer’s IT stack using artificial intelligence. These systems learn from humans. So, RPA software will develop and refine its executable actions by “watching” a user perform tasks inside an application’s user interface (UI).

The RPA agent is then able to emulate and repeat those actions. When you plug the RPA into the data analytics muscle that you know SAP is packing at the other end of the pipe with SAP HANA, you can see why SAP thinks RPA needs an I to make it more intelligent.

A Step Toward the Intelligent Enterprise

SAP has also laid down plans to release smart application design capabilities in the SAP Analytics Cloud solution and has added new partner content in the business content library. “With intelligent robotic process automation, our customers will be able to achieve the high automation level necessary to become an intelligent enterprise,” said Juergen Mueller, chief innovation officer at SAP.

“Machine learning acts here as the brain that is managing exceptions and guides the RPA bot to execute on desired processes. With our enterprise-grade offer for SAP Conversational AI, we have taken a step further than our previously announced industry-specific packaged bots. The expansion allows customers to automate their customer support with chatbots,” Mueller said.

Other Works of (Leonardo) Art

The last batch of updates were tabled at SAP TechEd Barcelona in October 2018. The promise from the SAP Conversational AI team is the ability to build fast and high-performing (and no doubt sophisticated) customer support bots in a matter of days.

SAP will now aim to produce “brain food” for its bot ventures by investing in machine learning (ML) capabilities for data scientists to train their own custom machine learning models.

“This is part of SAP’s strategy to move toward a single solution to deliver a unified machine learning experience across the SAP offering, with access to key open source machine learning technologies. This solution is intended to support easy deployment of machine learning models into production and at scale, easing the burden on IT organizations that manage the life cycle and integration of machine learning into their corporate environments,” said SAP in a press statement.

What’s the Big Picture for SAP Leonardo?

Five new machine learning services are planned for the remainder of 2018, including scene text recognition and customizable image segmentation, a trainable service to perform pixel-wise classification for the detection and recognition of objects in pictures and their shapes.

As well as working with Google on text-to-speech and speech-to-text services in this arena, SAP says it will now extend its connection points to the Google Cloud Platform throughout the last quarter of 2018.

As far as SAP is concerned with SAP Leonardo, the polymath can keep learning and developing new intelligence that is particular to specific tasks. And also, it is picking up intelligence that is differentiated across industry verticals. Polymath or not, SAP aims to make SAP Leonardo a work of art worthy of hanging in the enterprise software gallery of the future.

Curious how you can bring artificial intelligence to your customer support processes? Watch our recorded webcasts on SAP Leonardo. Or read about some real-world examples of machine learning in SAP Leonardo.