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Cognizant just introduced Cognizant Neuro Edge, an advanced addition to its Neuro suite of AI technologies designed to help businesses harness the power of AI and generative AI.

Edge computing allows enterprises to leverage computing power through sensors and devices within their networks, reducing reliance on centralized servers and the cloud. The Neuro Edge platform is engineered to support the entire edge AI value chain, from chips and devices to applications and business solution deployments. This is all designed to funnel up to business success long term.

Empowering enterprise businesses

Vibha Rustagi, Cognizant’s global head of IoT and engineering, stated that Cognizant Neuro Edge empowers enterprise businesses, particularly manufacturers, to integrate AI and generative AI into their operations, from hardware to applications. Rustagi emphasized that the Neuro Edge platform is a versatile framework designed to speed up the development of enterprise edge services.

“This can be done by abstracting the complexity of model selection by quantization, by fine-tuning of AI and GenAI models, and by RAG or retrieval augmented generation and so on agents that are compatible with edge devices,” Rustagi told CRN in a statement. “We’ve introduced edge compute which means faster accessibility to data and analysis of the data, and then real-time analysis of that.”

Key advantages of Neuro Edge

The key advantage of Cognizant Neuro Edge is that it provides businesses with essential hybrid GenAI cloud capabilities.

“Enterprises are increasingly embracing edge computing to enhance the responsiveness of their distributed devices and extract meaningful insights from the data they generate,” said Vibha in the press release announcing the platform. “Cognizant Neuro Edge is a powerful example of Cognizant’s leadership in developing a new approach to layering of on-board computing and processing with cloud services, paving the way for businesses to unlock a range of generative AI-driven benefits around operational efficiency, cost and risk reduction.”

Real-time interactions and operational stability

Neuro Edge enables real-time interactions with devices, which allows businesses to speed up decision-making, reduce data costs, and mitigate privacy risks while maintaining operational stability, even in low-bandwidth environments. The platform is cloud-agnostic, making it ideal for hybrid and multi-cloud environments, with computing power placed directly at the device. Key applications across industries include:

  • Healthcare and MedTech: Helping doctors make quick decisions with diagnostic sensors and offering on-device adjustments and recommendations based on patient data.
  • Energy and Telecommunications: Improving power plant operations, enhancing response to weather events, and boosting network security and automation to lower costs.
  • Logistics and Manufacturing: Enhancing fleet performance, cutting downtime with in-vehicle data processing, and predicting equipment failures to maximize uptime and save money.
  • Retail: Providing smart video analysis for real-time theft prevention and monitoring in-store traffic patterns to better serve customers.
  • Automotive: Enhancing the driver and passenger experience with real-time, context-aware, and private recommendations through cloud connectivity.

“We’re at an exciting time in the industry as the age of AI comes in full swing,” said Nancy Henriquez, head of U.S. community, SuperOps.ai. “Seeing the current capabilities and possibilities within SuperOps gets me more excited about how more platforms will leverage AI moving forward. There is no question, AI is augmenting and enhancing human capabilities and capacity, driving towards more efficiency than ever before. How the AI is targeted, fostered and allowed to learn, however, will be what sets platforms apart and determines the impact they have in business.”

Learn more about how generative AI is being implemented in the MSP space, with a special focus on whether it is ready to revolutionize MSP cybersecurity.