Cognizant Expands AI Capabilities with Neuro Edge Platform

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Cognizant has just launched Cognizant Neuro Edge, an advanced extension of its Neuro AI technology suite designed to help enterprises realize the potential of AI, including generative AI.

Edge computing enables enterprises to leverage compute power through sensors and devices on their networks, reducing reliance on centralized servers and the cloud. The Neuro Edge platform is designed to support the entire AI value chain at the edge, from chips and devices to applications and business solution implementations, all with the goal of driving long-term business success.

Supporting businesses

Vibha Rustagi, global head of IoT and engineering at Cognizant, said that Cognizant Neuro Edge enables enterprises, especially manufacturers, to integrate AI and generative AI into their operations, from hardware to applications. Rustagi emphasized that the Neuro Edge platform is a comprehensive framework designed to accelerate the development of enterprise edge services.

“You can do that by abstracting the complexity of model selection through quantization, through AI and GenAI model tuning, and through RAG or augmented generation of fetching and so on, agents that are compatible with edge devices,” Rustagi said in a statement to CRN. “We’ve brought edge computing, which means faster access to data and data analysis, and then real-time analysis.”

Neuro Edge’s main advantages

A key benefit of the Cognizant Neuro Edge solution is that it provides enterprises with essential hybrid GenAI cloud capabilities.

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

Real-time interactions and operational stability

Neuro Edge enables real-time interactions with devices, enabling companies to accelerate 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 compute power placed directly on the device. Key applications across industries include:

• Healthcare & MedTech: We help clinicians make quick decisions with diagnostic sensors and by offering device adjustments and recommendations based on patient data.

• Energy and Telecommunications: Improving power plant operations, increasing response to weather events, and increasing grid security and automation to reduce costs.

• Logistics and production: Increase fleet efficiency, reduce downtime with on-vehicle data processing, and predict equipment failures to maximize uptime and save money.

• Retail sales: We provide intelligent video analytics to prevent theft in real time and monitor store traffic to provide a better customer experience.

• Automotive: Improving the driver and passenger experience with real-time, context-aware recommendations delivered privately via cloud connectivity.

“We are at an exciting time in the industry as the era of AI is fully underway,” said Nancy Henriquez, US community lead, SuperOps.ai. “Seeing the capabilities and possibilities within SuperOps today makes me even more excited about how more platforms will leverage AI in the future. There is no doubt that AI is extending and improving human capabilities and abilities, leading to greater efficiencies than ever before. However, how AI is targeted, supported and allowed to learn will be what differentiates platforms and determines their impact on the business.”

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