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Break down IT/OT silos with the industry's first fully managed Edge AI solution to enable advanced AI use cases for industrial and manufacturing.
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Integrate and synthesize data from sensors, devices and systems into a single data plane to drive seamless on-premise processing and real-time decision making.
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Smaller, task-specific AI models provide easier access to advanced AI capabilities and reduce the cost and complexity of AI.
NTT DATA, a leading IT infrastructure and services company, has announced a new Edge AI platform that accelerates IT/OT convergence by bringing AI processing to the edge. This unique, fully managed solution processes data when and where it is generated, integrating disparate IoT devices, systems and data to enable real-time decision-making, improve operational efficiency and secure deployment of AI applications across industries, driving advanced Industry 4.0 technologies.
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“Furthermore, small, task-specific AI models help drive the democratization of AI by making it easier for businesses to deploy AI where and when they need it, without having to massively overhaul their entire infrastructure.”
While there has been a lot of attention on GenAI and large language models (LLMs), these technologies are impractical for industries that require real-time, local decision making. NTT DATA's Edge AI solutions address this challenge by processing massive data sets on compact computing platforms and delivering real-time AI insights using smaller, more efficient machine learning models.
NTT DATA's Edge AI is a comprehensive managed service platform with all the systems, tools and capabilities required for Edge AI: data discovery, collection, integration, computational power, seamless connectivity and AI model management.
Supported by NTT DATA's consulting data scientists, managed services and global technical resources, our Edge AI platform addresses shadow IoT challenges and AI infrastructure requirements by automatically discovering, integrating and processing data from IoT devices and IT assets across the organization, simplifying AI deployment and management.
Solve industry-specific challenges with AI-driven insights
Designed to support industry-specific requirements, the Edge AI platform leverages lightweight, cost-effective AI models to run within a small computing box. Edge AI performs specific tasks such as supporting safety and operational efficiency by collecting data from various devices across the network environment, enabling instant, secure data processing and analysis.
Manufacturing industries can benefit from improved predictive maintenance by accessing IT/OT data from sensors, machines, cameras and applications to plan and respond to breakdowns. Additionally, NTT DATA's Edge AI can monitor and optimize energy consumption in real time, predicting energy spikes to optimize machine usage, reducing costs and CO2.2 Reducing emissions through renewable energy.
“Our Edge AI platform represents a major leap forward in securely and cost-effectively driving AI at the edge,” said Shahid Ahmed, group executive vice president, Edge Services, NTT DATA. “By harmonizing data from disparate sensors and devices with lightweight AI models to power a full range of automation use cases, NTT DATA's Edge AI is spearheading the adoption of industrial AI as the first fully managed service, helping organizations modernize with customized industry-specific solutions.”
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Seizing the $200 billion market opportunity
According to IDC, global spending on edge computing is expected to reach US$232 billion in 2024, up 15% from 2023. This growth will be sustained by the increasing number of connected IoT devices around the world, which is expected to exceed 41 billion by 2025.
NTT DATA is poised to capture significant market share through its dedicated IoT consulting and services business that brings together 1,000 industry experts and hundreds of use cases including predictive maintenance, fleet management, connected factories, energy consumption monitoring and sustainability, and has already trained over 500 sales experts worldwide to accelerate its Edge AI go-to-market efforts.
NTT DATA's Edge AI deployment approach offers customers 30 days of free discovery and diagnosis of their IT and OT environments. The software auto-discovers assets using a vast library of pre-built OT interfaces. After this initial phase, the Edge AI software generates a comprehensive diagnostic report that includes an inventory of assets and data streams, including identifying security risks and vulnerabilities.
“A key challenge for enterprises is to securely and reliably collect, aggregate and turn operational data into actionable insights across a fragmented environment of devices, platforms and data sources,” said Alejandro Cadenas, associate vice president, Telecom Mobility & IoT Research, IDC Europe. “NTT DATA's Ultra-Light Edge AI addresses these issues, simplifying the deployment and adoption of data-driven enterprise strategies, reducing risk and timelines, and optimizing total cost of ownership and value for enterprises.”
First fully managed service advances secure AI deployment at the edge
NTT DATA's managed services for Edge AI provide a unified view and management of devices, sensors and assets. With expert support and advanced technology, NTT DATA helps businesses simplify complex processes, reduce costs, improve performance and accelerate their digital transformation.
Edge AI, the industry's first fully managed IT/OT convergence platform, transforms physical assets into software assets to deliver data-driven insights, regardless of manufacturer. Managed services running at the edge integrate OT assets with IT applications to drive operational efficiency. Edge AI also displays firmware versions on all connected devices to facilitate vulnerability patching and security across devices.
“Computing and AI must take place where it creates the most value for the enterprise, and for many industrial companies, this is where the data is generated. By ingesting IT and OT data and leveraging AI models to drive use-case specific outcomes, NTT DATA's solution takes the Industry 4.0 vision another step closer to being able to deliver,” said Pablo Tomasi, principal analyst, private networks at Omdia. “Furthermore, having small, task-specific AI models makes it easier for enterprises to deploy AI where and when they need it, without the need for a wholesale overhaul of their entire infrastructure, helping to further the democratization of AI.”
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