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May 13, 2019
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Alten, European leader in Engineering and Technology Consulting helps its customers for over 25 years to enhance their competitiveness.
whitePaper | July 10, 2020
There’s no arguing that preventing failures and accidents is critical for industry. Unexpected incidents can grind operations to a halt for extended periods of time and necessitate expensive repairs. Just 12 hours of downtime for an oil production platform could cost six to eight million dollars in lost production opportunity alone. A single day of grounding for a plane costs roughly four to five million dollars. Because of these disruptions, industrial sectors are always on the lookout for newer, better maintenance methods, and the approach on everyone’s lips right now is predictive maintenance. While everyone agrees on the name, there is less consensus on what it means or how to implement it. But to truly unlock the potential of predictive maintenance, it needs to be paired with artificial intelligence (AI) and machine learning (ML).
whitePaper | June 30, 2022
Low code and no code (LCNC) development platforms expedite the creation of new applications with minimal or no coding requirements, as well as offer tools for non-programmers to create applications of their own. Low code development was introduced in the early 2000s to increase developer productivity. It uses a variety of approaches that automate and abstract application development activities, such as drag and drop editors, code generation, component assembly and model-driven development.
whitePaper | December 6, 2022
The impact of system downtimes is rapidly rising due to businesses’ increased dependency on data and technology. It can cause loss of opportunities, productivity loss, confidence erosion, SLA penalties, supply chain ripple effects, and most importantly, a damaged reputation.
whitePaper | January 12, 2020
“The services market for artificial intelligence technologies is rapidly maturing on the back of several years of learning and a realization—delivering AI is unlike delivering any other technology thus far. Delivering on the promise of AI calls for far more collaboration between service providers, tech vendors, and enterprise clients.” The biggest differentiator in enterprise AI services, as described by most of the customer leaders, is the quality of people—not just the quantity available for a specific skill. Domain understanding and data engineering capabilities are top priorities. A culture of innovation, experimentation, collaboration, and co creation with customers is the key winning formula here.”
whitePaper | August 9, 2020
The payments industry is going through a period of massive disruption. Consumers increasingly expect a fast, easy payment process, coupled with immediate, uninterrupted access to account information and services.
whitePaper | August 26, 2022
Started in 2013, Arya.ai is the first deep learning (DL) startup in India and has been one of the very early adopters to use DL in Financial Institutions. AryaXAI by Arya.ai, a full stack ML Observability platform, offers multiple components - AI explainability, ML monitoring, ML audit and Policy controls, which organisations require beyond simple ML monitoring tools.
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