SAP has announced the acquisition of Contextor SAS in a bid to boost the company's machine learning and robotic automation portfolio. On Monday, the software solutions provider said the purchase will help SAP accelerate the development of the Leonardo machine learning solution, a platform for the creation of enterprise machine learning and automation-based apps and software. Financial details were not disclosed. Contextor SAS, based in Orsay, France, is a small European company focused on robotic process and desktop automation, offering products which are compatible with Microsoft Remote Desktop setups, XenDesktop workstations, and XenApp application servers. Founded in 2000 by Patrick Lemare, Contextor now accounts for over 100,000 bot deployments using automation for business processes.
With each delivery cycle, measure the results, see the impact of AI, and use that to raise awareness with the C-Suite on how AI can transform operations. Many packaged cognitive services, such as optical character recognition, sentiment analysis, or speech to text, are very easy to implement. However, to leverage these appropriately, one must understand how each solution can fit within overall business processes and where it must be applied to accelerate intelligent automation. Beyond plug-and-play cognitive services, organizations can start to explore custom machine learning algorithms to create unique predictive models based on their business data. Accessing the technology to enable this is straightforward, but understanding an organization's unique data and process requirements to apply machine learning to maximum impact remains the biggest challenge.
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SAN FRANCISCO – Although artificial intelligence (AI) is a nascent science today, it is already transforming industries--and nowhere is this truer than healthcare, which will change beyond anyone's imagination. Healthcare companies are using AI to reduce costs and improve patient outcomes, compared to traditional predictive analytics and rules-based software. Additional AI implementations include disease prediction and intervention, network steerage to match patients to optimal providers for best outcomes, and real-time intervention to create better outcomes for high-risk patients. AI adoption for new and existing healthcare products promises to have a profound impact in improving consumer digital and provider experiences. This will be accomplished by automating--or even eliminating--abrasive transactions and reducing administrative cost structures through intelligent interactions, as well as the automation of manual work.
The unbridled enthusiasm for digital transformation has prompted enterprises to storyboard roadmap to embrace the next wave of technology. The pace at which technology is mushrooming around, enterprises are in the dire need of automating labor-intensive business processes. This is where Robotic Process Automation-led digital transformation has acquired the center stage. RPA successfully replicates human actions to handle heaps of repetitive tasks that normally involves multiple human resources fully engrossed in completing them without adding noticeable business value. Needless to mention AI, machine learning and other technologies have emerged on the scene to make this happen, and yet Robotic Process Automation has proved to be impactful as it can smartly mimic human actions and perform mundane technical tasks and thereby evolving workforce to perform other high-value tasks.