TOKYO, Mar 2, 2026 - (JCN Newswire) - Mitsubishi Heavy Industries, Ltd. (MHI) and SoftBank Corp. (SoftBank) today announced the launch of a demonstration experiment using SoftBank's AI-RAN product(1) "AITRAS" to deploy edge AI applications(2) within the edge data center(3) "DIAVAULT" solution installed at MHI's Yokohama Hardtech Hub (YHH). This demonstration will verify the effectiveness of high-speed AI inference executed over a secure and stable communication environment isolated from external networks in an on-premises(4) setting.

Furthermore, both companies have agreed to integrate MHI's highly scalable edge data center facility technologies with "AITRAS" to enable AI execution in real-world environments, aiming for social implementation of a new AI infrastructure.

Background of Collaboration

In recent years, efforts to enhance the operation and maintenance of equipment through AI, referred to as "AI Transformation," have accelerated across various industries, including energy and industrial machinery. To utilize AI effectively in such real-world environments, there is a growing demand for data centers that can be installed closer to the operational sites and provide an AI execution environment that balances stable communication and data security.

Overview of Demonstration Experiment

The Edge Data Center "DIAVAULT" in YHH

In response to these practical challenges, as the first step of this collaboration, an AI-RAN environment using "AITRAS" will be constructed within the on-premises "DIAVAULT" solution. An AI application developed by MHI that can "Defect Detection & Repair AI Application for Mitsubishi Heavy Industries Products" will be deployed within this environment for demonstration testing.

During the demonstration, image and video data sent from field workers' smart devices will be analyzed in real-time within the closed network environment to identify fault locations and suggest appropriate repair methods.

Value Delivered by This Demonstration

Through this demonstration, the following three points will be validated:

1. Real-time analysis through edge AI processing
AI processing is completed within the closed network without passing through the cloud, significantly reducing data transmission and analysis latency under a stable communication infrastructure.
2. Enhanced security and closed network environment
A secure AI inference environment is established that prevents confidential product data from leaving the company.
3. Efficiency and standardization of repair operations
AI-based fault identification reduces the operational burden that previously relied on the expertise of skilled technicians.

Future Outlook

Building on this collaboration agreement and demonstration experiment, both companies will leverage their respective strengths to develop a scalable and reliable edge AI operational platform that continuously adapts to AI advancements. They will also promote initiatives to accelerate customers' on-site "AI Transformation" through the creation of innovative solutions.

(1) A technology concept that realizes both RAN (Radio Access Network) control functions and AI server functions on the same hardware platform. "AITRAS" is an integrated AI-RAN product that provides high-capacity, high-performance, and high-quality communication networks at carrier grade and also enables the provision of AI applications.
(2) Applications that perform data processing and AI inference at the site where the data is created, rather than in the cloud.
(3) A small-scale data center installed close to users and devices.
(4) A system where servers are placed at sites such as companies, factories, or research institutes rather than in the cloud, allowing direct management and processing of data.

- SoftBank, the SoftBank name and logo are registered trademarks or trademarks of SoftBank Group Corp. in Japan and other countries.

- Other company, product and service names in this press release are registered trademarks or trademarks of the respective companies.

About MHI Group

Mitsubishi Heavy Industries (MHI) Group is one of the world’s leading industrial groups, spanning energy, smart infrastructure, industrial machinery, aerospace and defense. MHI Group combines cutting-edge technology with deep experience to deliver innovative, integrated solutions that help to realize a carbon neutral world, improve the quality of life and ensure a safer world. For more information, please visit www.mhi.com or follow our insights and stories on spectra.mhi.com.

TOKYO, Feb 27, 2026 - (JCN Newswire) - NEC Corporation (NEC; TSE: 6701), in collaboration with Pegatron Corporation (Pegatron; 4938.TW) and Edgecore Networks, has obtained Bronze Badge certification from the Telecom Infra Project (TIP) for its new hardware products: Endeavor (Pegatron MPND400-2) and AMX3200 (Edgecore), components of the open and disaggregated 400G optical transponder platforms known as Phoenix, demonstrating the continued expansion of NEC's ecosystem portfolio.

TIP is a global collaborative community advancing the development and deployment of open, disaggregated, and interoperable telecommunications infrastructure.

The Phoenix solution is a standard specification defined by TIP's Open Optical and Packet Transport (OOPT) Project Group, that includes NTT, Telia, Telefonica, Vodafone, Deutsche Telekom, and MTN. OOPT is an operator-driven initiative responsible for the development of technical requirements and focused on the growth of open technologies, architectures, and interfaces in the optical and IP networking domains.

NEC’s Phoenix Solution consists of the NEC Network Operating System (NOS), white box hardware, and third-party optical transceivers, enabling highly flexible and scalable network deployments. The newly added Endeavor and AMX3200 platforms are both 1U-height white boxes designed for standard 19-inch rack mounting. Each is equipped with four CFP2-DCO ports supporting 400G coherent pluggable transceivers, enabling transmission capacity of up to 1.6Tbps per device for Wavelength Division Multiplexing (WDM) applications.

The NEC NOS is universally deployed on Phoenix-certified white box platforms, providing advanced hardware management and supporting open APIs such as OpenConfig and YANG data models to ensure seamless integration and automation for network operators.

The NEC NOS has previously been awarded the TIP Phoenix Gold Badge in combination with the Galileo Flex-T white box. The new Bronze Badge certifications for Endeavor and AMX3200 further strengthen the Phoenix ecosystem, enabling network operators to benefit from a truly multi-vendor environment and enhancing the reliability and flexibility of optical transport networks.

Phoenix disaggregated 400G transponder solution
- NEC & Partner Eco-system -

"The Bronze Badge certification for the Endeavor and AMX3200 platforms further highlights the robustness of our optical networking solution ecosystem," said So Sato, Senior Director, Network Solutions Business Division, NEC Corporation. "This achievement demonstrates the value of openness, affirming our commitment to supporting operators with flexible solutions that meet diverse networking needs."

"The Telecom Infra Project is excited to see the broader impact of TIP’s Phoenix open transponder design across the industry. This new hardware solution greatly enriches the open transponders ecosystem by offering operators multiple choices to deploy this solution at scale," said Arturo Mayoral, Head of Transport Technology at TIP. "We are especially proud to see how the TIP test and validation program is enabling the community to accelerate interoperability among open solutions while reinforcing market confidence in their maturity and reliability."

"We are proud to achieve TIP Phoenix Bronze Badge certification for Pegatron’s Endeavor MPND400-2 muxponder in collaboration with NEC," said Dr. James Shue, SVP & CTO of Pegatron. "This certification validates our commitment to delivering high-quality, standards-based optical networking hardware for the open and disaggregated ecosystem. Pegatron remains dedicated to advancing open optical networking solutions that provide operators with greater flexibility and choice."

"Edgecore Networks is proud to expand our collaboration with NEC through the Phoenix ecosystem. Achieving TIP Bronze Badge certification for the AMX3200 underscores our shared commitment to delivering open, scalable, and interoperable optical transport solutions," said Nanda Ravindran, VP of Product Management and Planning of Edgecore. "By combining Edgecore’s open hardware innovation with NEC’s proven NOS and system integration expertise, we are empowering operators worldwide to accelerate network modernization with greater flexibility, efficiency, and confidence.

"These research results were obtained from a grant program (No.JPJ012368G50311) by the National Institute of Information and Communications Technology (NICT), Japan.

About NEC

The NEC Group leverages technology to create social value and promote a more sustainable world where everyone has the chance to reach their full potential. NEC Corporation was established in 1899. Today, the NEC Group’s approximately 110,000 employees utilize world-leading AI, security, and communications technologies to solve the most pressing needs of customers and society.

For more information, please visit https://www.nec.com, and follow us on LinkedIn and YouTube.

TOKYO, Feb 27, 2026 - (JCN Newswire) - NEC Corporation (NEC; TSE: 6701) has successfully demonstrated a technology in which Agentic AI autonomously manages the entire lifecycle of the User Plane Function (UPF)*, a primary function of 6G/5G core networks, from design, construction, and deployment through to operational monitoring. This research achievement was realized in collaboration with Amazon Web Services (AWS).

Based on NEC’s expertise and experience in communications service provider networks, this demonstration was achieved by leveraging "Kiro," an AWS agentic AI with an integrated development environment (IDE) and command-line interface (CLI). As a result, NEC confirmed that the time required from network design to initial service launch, which previously required several weeks with manual configuration by network operators, can be significantly reduced to just a few hours. In addition, automated anomaly detection and self-healing operations without human intervention were also verified using an AWS AI tool. These results demonstrate that automated orchestration of UPF utilizing an AWS AI tool contributes to reducing deployment burden for communications service providers (CSPs), improving operational efficiency, and accelerating service rollout.

Traditionally, building and deploying network functions required extensive manual configuration and advanced technical expertise, placing a heavy burden on network operators at CSPs. These manual processes also increased the risk of human error, which complicated fault isolation and recovery during network incidents. These issues contributed to longer service rollout timelines and rising operational costs.

Key Features

1. Autonomous UPF Deployment and Operation Enabled by AI

Drawing on expertise gained through designing, building, and operating commercial carrier networks, NEC embedded this knowledge into AI models capable of automatically generating and executing UPF deployment procedures. This enables not only automation of operational tasks but also supports truly autonomous network operations suitable for production environments.

2. Flexible Deployment Enabled by Cloud-Based Operational Models

By leveraging AWS, NEC can apply cloud-native operational models directly to CSP environments, enabling flexible deployment across networks, including edge locations and on premises systems.

Benefits / Value

• Reduces network function deployment time from weeks to hours—from network design to initial service launch (compared to traditional manual deployment methods at NEC)
• Minimizes human error and improves operational quality through automation
• Allows personnel without deep technical expertise to deploy and operate network functions, helping address labor shortages
• Supports CSPs with rapid service launches and maximizes revenue opportunities

This initiative represents an important achievement as a foundational technology for realizing autonomous network operations required in the future 6G era. Looking ahead, NEC will continue to take on new technological challenges based on its vision of being "AI Native," addressing the challenges that communications service providers may face both today and in the future as networks become increasingly complex.

A demonstration based on the verified environment will be showcased at the AWS booth during MWC Barcelona 2026 (March 2–5, 2026), the world’s largest mobile industry event.

"The telecommunications industry is at an inflection point where AI-driven automation is becoming essential to build a competitive advantage by serving the end-customers faster and reducing the operating costs. NEC's breakthrough in autonomous UPF orchestration demonstrates how AWS AI services can fundamentally transform network operations, enabling communications service providers to deploy complex 5G infrastructure in hours rather than weeks. This level of automation democratizes advanced network deployment capabilities, allowing operators to serve the ever-increasing capacity needs and focus their innovation efforts on service differentiation rather than manual configuration and operational tasks. This collaboration with NEC exemplifies the intelligent automation that will define the next generation of telecommunications infrastructure."
-Amir Rao, Global Director, GTM and Telco Solutions at Amazon Web Services

"Validating the automation of UPF deployment and operations using AI and GitOps in an AWS environment is an important accomplishment for NEC. This technology does more than just improve operational efficiency. By embedding the design and operational expertise that NEC has cultivated through commercial networks into AI, we aim to enable autonomous operations and achieve a significant improvement in end-to-end efficiency across UPF deployment and operations, including on-site activities. NEC will continue to contribute to the realization of autonomously operable mobile networks that are required for the 6G era, providing environments that allow communications service providers to focus on creating service value."
- Takashi Sato, Corporate Senior Vice President and Managing Director, Network Solutions Business Division of NEC Corporation

A portion of the technologies used in this project were obtained from a grant program (No. JPJ012368G50701) by the National Institute of Information and Communications Technology (NICT), Japan.

(*) User Plane Function: The processing of user data traffic in the 5G Core Network (5GC).

About NEC

The NEC Group leverages technology to create social value and promote a more sustainable world where everyone has the chance to reach their full potential. NEC Corporation was established in 1899. Today, the NEC Group’s approximately 110,000 employees utilize world-leading AI, security, and communications technologies to solve the most pressing needs of customers and society. For more information, please visit https://www.nec.com, and follow us on LinkedIn and YouTube.

TOKYO, Feb 27, 2026 - (JCN Newswire) - NEC Corporation has expanded the capabilities of its User Plane Function (UPF, *1) for telecom operators by adding support for second-generation AWS Outposts racks (*2), further strengthening its multi deployment model. With this enhancement, NEC’s UPF can now operate consistently across on-premises environments, the cloud, edge locations, and AWS Outposts racks installed within operators’ network sites. This enables flexible deployment design that is tailored to traffic characteristics and service requirements.

NEC’s UPF is designed for lightweight, high performance operation in telecom networks, achieving 200 Gbps throughput while limiting CPU usage to only 20% of total CPU cores on second generation AWS Outposts racks. This lightweight architecture enables easier coexistence with other workloads on second-generation AWS Outposts racks and supports the deployment of low-latency, edge-based services such as network slicing and service application integration. These capabilities have been achieved through close collaboration with Amazon Web Services (AWS).

Another key feature of NEC’s UPF is its unified software architecture, which delivers a consistent experience from edge sites to centralized deployments. The same software can be used when deployed on second generation AWS Outposts racks, ensuring network wide consistency in design and operations. With a cloud optimized approach that incorporates continuous updates and automated operations, NEC enables labor efficient, stable, large scale network operation. This supports telecom operators’ diverse network strategies, from leveraging existing infrastructure to adopting cloud native architectures.

With edge deployments expected to accelerate in the 6G era, NEC has combined expanded cloud adoption options enabled by second-generation AWS Outposts racks with the space- and power-efficient design of its UPF to achieve efficient edge rollouts and the integration of edge environments with cloud services.

The provision of this solution helps to advance NEC’s "AI Native" vision for society and contributes to solving social challenges.

"NEC's innovative approach to User Plane Function deployment exemplifies how AWS Outposts enables telecommunications operators to modernize their infrastructure without compromising on the application's mission-critical performance or the operational consistency delivered by the cloud. With second-generation AWS Outposts, NEC delivers the cloud-native agility that operators need while maintaining the low-latency, high-throughput performance that 5G services demand. This collaboration demonstrates AWS's commitment to helping telecommunications partners build mission critical, high-performance, flexible, and scalable networks that will power the next generation of connected experiences."
- Amir Rao, Global Director, GTM and Telco Solutions at Amazon Web Services

"Enabling NEC’s UPF, which is designed for multi-platform environments, to run on second-generation AWS Outposts racks will expand the range of choices that communications service providers have for network design and operations. The UPF supports both rapid service deployment and stable operations while minimizing design and operational complexity, thereby strengthening service providers’ ability to deliver reliable services. Going forward, NEC will continue to pursue the realization of network platforms that seamlessly and pragmatically integrate cloud and network technologies, contributing to value creation for communications service providers."
- Takashi Sato, Corporate Senior Vice President and Managing Director, Network Solutions Business Division of NEC Corporation

A portion of the technologies used in this project were obtained from a grant program (No. JPJ012368G50701) by the National Institute of Information and Communications Technology (NICT), Japan.

*1)User Plane Function: The processing of user data traffic in the 5G Core Network (5GC).
*2)AWS Outposts is a family of fully managed solutions that brings AWS infrastructure and services to virtually any on-premises or edge location for a consistent hybrid experience. Second-generation AWS Outposts racks deliver up to 40% better compute performance than the first generation, simplify network operations, enable cost-efficient scaling of on-premises workloads, and are optimized for ultra-low-latency, high-throughput requirements.

About NEC

The NEC Group leverages technology to create social value and promote a more sustainable world where everyone has the chance to reach their full potential. NEC Corporation was established in 1899. Today, the NEC Group’s approximately 110,000 employees utilize world-leading AI, security, and communications technologies to solve the most pressing needs of customers and society. For more information, please visit https://www.nec.com, and follow us on LinkedIn and YouTube.

Highlights:

• Integration of the proposed technologies will help address the transmission and computational infrastructure challenges faced when implementing AI agents.
• This trial verified the effectiveness of optimizing the transmission and computational processing of high-volume data handled by AI agents.
• This initiative has been selected for exhibition at the Japan Pavilion at MWC 2026, where the research findings and underlying concept will be presented to an international audience.

TOKYO, Japan, Feb 26, 2026 - (JCN Newswire) - The Graduate School of Engineering, The University of Tokyo (Tokyo; Dean of the Graduate School of Engineering: Professor Yasuhiro Kato; Head of the Nakao Research Laboratory: Professor Akihiro Nakao; hereinafter "The University of Tokyo"), NTT, Inc. (Headquarters: Tokyo; President and CEO: Akira Shimada; hereinafter "NTT"), and NEC Corporation (Headquarters: Tokyo; President and CEO Takayuki Morita; hereinafter "NEC") have integrated three newly proposed technologies on a 6G(*1)/IOWN(*2) platform to realize the widespread use of AI agents(*3) supporting a safer and more secure society. Through this initiative, the three parties have combined streaming semantic communication technology(*4), AI-oriented media control technology(*5), and In-Network Computing (INC) architecture technology(*6) to optimize the high-volume data transmission and computational processing required for AI agents. The effectiveness of these technologies has been quantitatively verified through a trial, and plans are slated for this initiative to be showcased at the Mobile World Congress 2026 (MWC 2026) Japan Pavilion, where the research findings and underlying concept will be presented to an international audience.

Figure 1. Overview of the technologies integrated on the 6G/IOWN platform

1. Background and significance of this three-party collaboration

International collaboration and global standardization are vital to the advancement of telecommunications, which serves as a universal platform accessible to anyone, anywhere in the world, and should therefore be considered from a global value perspective. In recent years, the importance of safety and security has grown, as both offer global value.

To realize a safer and more secure society, the ability to quickly perceive and take appropriate action in response to disasters, accidents, cyberattacks, and other rapidly evolving situations is imperative. However, relying solely on personnel and predefined rules to respond to such situations has its limitations, making the use of AI essential. Utilizing AI agents enables autonomous, real-time perception of the situation at hand, helping to prevent potential damage and minimize the impact of any damage that does occur.

Meanwhile, next-generation ICT infrastructure capable of processing and transmitting massive amounts of data with low latency and high reliability is vital to enhancing the functionality of AI agents.

Against this backdrop, The University of Tokyo, NTT, and NEC—all three of which possess strengths in 6G and IOWN—have united under The University of Tokyo’s Social Cooperation Program to conduct research and development on 6G and IOWN platform technologies to realize AI agents supporting safety and security.

2. Research background

While the use of AI in recent years has primarily centered on models that act based on human prompts, the utilization of AI agents capable of acting autonomously based on sensor data and other non-human-originated inputs without relying on specific instructions from human operators is expected to become increasingly common in the society of the future. In turn, these advancements will enable the realization of AI agents that support safety and security by continuously collecting and monitoring data from the surrounding environment and responding in real time when signs of abnormalities are detected.

However, the expanded use of continuously operating AI agents will cause the amount of multimodal data(*7) to skyrocket, and existing ICT infrastructure is not equipped to support such a drastic increase in data due to the technological challenges listed below.

(1) Insufficient wireless bandwidth

Continuous transmission of vast amounts of data from countless sensors and devices makes it difficult to secure sufficient wireless bandwidth.

(2) Increasing computational load due to round-the-clock AI processing of sensor data

If all sensor data is continuously processed using computationally intensive AI, it will cause an excessive computational load, making it difficult to respond in real time.

(3) Increasing computational load and power consumption with large-scale AI

Large-scale AI is required to analyze a wide range of sensor data, thereby increasing the need for computational capabilities and electrical power.

3. Technology highlights

In this research, the three parties proposed the following technological approaches to resolve the aforementioned challenges.

(1) Streaming semantic communication technology (The University of Tokyo)

This applied form of semantic communication detects contextual changes and transmits only semantic differences, thereby reducing wireless communication resources dramatically.

(2) AI-oriented media control technology (NEC)

Assigning a data identifier to an AI agent and then selectively feeding only key sensor data to the AI agent reduces the computational resources required for inference. Learning inference results from the AI agent, the data identifier is able to identify critical sensor data.

(3) In-Network Computing (INC) architecture technology (NTT)

Rather than relying on a single massive AI model, highly efficient and reliable AI processing is made possible by combining small, specialized AI distributed across the network with external information sources.

Figure 2. Technological challenges and the proposed approach

4. Trial Overview

This trial was conducted to verify the impact of the proposed technologies in terms of reducing latency through the improvement of transmission and computational processing efficiency, taking into account the characteristics of end-to-end latency(*8) (E2E latency) when using AI agents. In this trial, a video dataset including critical situations (60 seconds; 1,800 frames) was used to conduct a phase-by-phase evaluation of the configuration with which an AI agent processes video input from sensors. The intended use cases are scenarios requiring real-time performance where an AI agent continuously monitors the surroundings of a user wearing augmented reality (AR) glasses to identify environmental and contextual changes that can be used to predict and assess risk indicators.

First, the latency characteristics in a configuration where all frames fed from a sensor were sequentially processed using AI were assessed as a preliminary evaluation. The results confirmed that processing wait time increases cumulatively with each frame, resulting in a tendency for E2E latency to build over time. This implies an increase in the amount of time it takes from the occurrence of a critical situation in front of the user until assessment results and guidance are provided, thus revealing that this could pose an issue in use cases involving real-time AR assistance.

Next, on the basis of the results of the preliminary evaluation, a system configuration was assessed in which the proposed technology was applied in this trial. The evaluation confirmed that both communication traffic and computational load were reduced, and that E2E latency could be maintained at an almost constant level throughout the entire video stream. In addition, no tendency was observed for processing wait times to increase cumulatively. Furthermore, no degradation in AI inference accuracy was detected as a result of applying the proposed technology. These results demonstrate that, for this use case, which requires real-time performance, the proposed technology can stably reduce E2E latency while maintaining AI inference accuracy.

Figure 3.1. Use of AR glasses in the trial        Figure 3.2. AR glasses display

5. Roles and Responsibilities

(1) The University of Tokyo:

Responsible for research and development of streaming semantic communication technology, primarily contributing to addressing technical challenges related to bandwidth constraints in wireless network segments.

(2) NEC:

Responsible for research and development of AI-oriented media control technology primarily contributing to addressing the technical challenge of increased computational load resulting from continuous AI processing of sensor data.

(3) NTT:

Responsible for research and development of In-Network Computing (INC) technology, primarily contributing to addressing technical challenges related to increased computational load and power consumption associated with the scaling of AI models.

Through the interaction and integration of each party’s technologies, the collaboration has also enabled contributions to addressing additional technical challenges beyond their primary areas of responsibility.

6. Future outlook

This initiative has been selected for exhibition at the Japan Pavilion at MWC 2026, where the research findings and underlying concept will be presented to an international audience.

Going forward, with a view toward the social implementation of the research findings, the three parties will accelerate research and development aimed at realizing AI agents and next-generation ICT infrastructure that support safety and security.

Notes:

*1.6G
6G (sixth-generation mobile communication systems) refers to next-generation mobile communication technologies currently under research as the successor to 5G. In addition to ultra-high speed, ultra-low latency, and high reliability, 6G is expected to provide a communications infrastructure designed to support massive device connectivity and AI-native applications.
*2.IOWN (Innovative Optical and Wireless Network)
The IOWN concept envisions a network and information processing infrastructure, including end devices, that optimizes both individuals and systems as a whole based on diverse information. By leveraging innovative technologies centered on optical communications, IOWN aims to provide ultra-high-speed, large-capacity communications and vast computational resources.
*3.AI Agent
An AI agent is an AI technology that understands objectives based on surrounding conditions and input data, and autonomously makes decisions and takes actions to execute tasks. In addition to conventional AI systems that operate based on human-issued instructions (prompts), growing attention is being given to AI agents that continuously perceive and assess their environment using non-human-originated inputs, such as sensor data.
*4.Streaming semantic communication technology
Semantic communication is a communication method that focuses on the meaning and importance of data, extracting and compressing only the necessary information for transmission. Compared with conventional bit-level communication, it significantly reduces communication volume while efficiently transmitting information required for AI processing. Streaming semantic communication technology is an applied form of semantic communication that detects changes in surrounding context and transmits only semantic differences, thereby dramatically reducing communication resource usage in wireless segments.
Related publication:
Shota Ono, Akihiro Nakao, "Semantic Communication Scheme for Real-Time Video Streaming Considering Temporal Semantic Continuity," IEICE Technical Report, March 2026 (in Japanese).
*5.AI-oriented media control technology
AI-oriented media control technology analyzes input data, such as sensor data and video, prior to AI processing and selectively filters it based on importance and necessity. This reduces the computational load required for AI inference, enabling improved real-time performance and more efficient use of computing resources.
Related publication:
K. Azuma, H. Itsumi and K. Nihei, "Similarity-based Frame Screening for Edge-Cloud In-Cabin Monitoring," In Proc. of 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA, 2026.
*6.In-Network Computing (INC) architecture technology
In-Network Computing (INC) is an architecture that integrates computational functions, such as AI processing, within the core of mobile networks, allowing critical processing to be completed inside the network. By effectively utilizing distributed computing resources across devices, networks, and cloud systems, INC enables low-latency and highly reliable service delivery.
Related publications:
Kentaro Hayashi, Shiku Hirai, Tatsuya Matsukawa, and Hiroki Baba, "High-Speed End-to-End Information Synchronization and Collaboration Technology ‘In-Network Service Acceleration Platform’ for the 6G/IOWN Era," NTT Technical Journal, October 2024 (in Japanese).Kentaro Hayashi, Shota Ono, Tomonori Takeda, Akihiro Nakao, "Network and Cost-Aware Tool Selection System for MCP-Integrated LLM," IEICE Technical Report, December 2025. (in Japanese).
Hiroki Baba, Kentaro Hayashi, Shiku Hirai and Tomonori Takeda, "Unified Control of Network and Compute Toward 6G In-Network Computing Service," In Proc. of 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA, 2026.
*7.Multimodal data
Multimodal data refers to data that combines multiple types (modalities) of information, such as video, audio, sensor data, and location information.
*8.End-to-end latency
End-to-end latency refers to the total time required for data to be transmitted from the source, processed at the destination, and returned as a response. It includes both communication latency and computational processing latency, and is a critical metric for AI services that require real-time performance.

About The University of Tokyo

The University of Tokyo is Japan's leading university and one of the world's top research universities. The vast research output of some 6,000 researchers is published in the world's top journals across the arts and sciences. Our vibrant student body of around 15,000 undergraduate and 15,000 graduate students includes over 5,000 international students.

About NTT

NTT contributes to a sustainable society through the power of innovation. We are a leading global technology company providing services to consumers and businesses as a mobile operator, infrastructure, networks, applications, and consulting provider. Our offerings include business consulting, agentic AI solutions, managed application services, cloud, data center and edge computing, all supported by our deep global industry expertise. We are over $90 billion in revenue and 340,000 people, investing 30% of our profits into fundamental research and development each year. Our operations span across 70+ countries and regions, allowing us to serve clients in over 190 of them. We serve 75% of Fortune Global 100 companies, thousands of enterprises, government clients and millions of consumers.

About NEC Corporation

The NEC Group leverages technology to create social value and promote a more sustainable world where everyone has the chance to reach their full potential. NEC Corporation was established in 1899. Today, the NEC Group’s approximately 110,000 employees utilize world-leading AI, security, and communications technologies to solve the most pressing needs of customers and society. For more information, please visit https://www.nec.com, and follow us on LinkedIn and YouTube.

TOKYO, Feb 26, 2026 - (JCN Newswire) - NEC Corporation (NEC; TSE: 6701), a leading global IT and network transformation services provider, today announced that it has been selected by Eletronet, an Axia Energia company and widely recognized Brazilian Telecom and IT infrastructure provider, to modernize its optical backbone with the deployment of Nokia's optical solutions. The project adds 8,000 kilometers of new fiber routes. This expansion will reach a total of 26,000 kilometers across 23 Brazilian states, covering all regions of the country by the end of 2026. The network will be upgraded with the Nokia 1830 Photonic Service Switch (PSS) and Nokia 1830 Global Express (GX) platforms to further enhance infrastructure reliability and stability. The modernization will enable services with speeds of up to 1.2 Tb/s per optical channel and ensure higher quality data transport. Project integration, including work coordination and equipment deployment, will be led by NEC as the system integrator.

Eletronet is investing BRL 157 million (USD 30.4 million) in this initiative to reinforce its role as a neutral connectivity hub. The infrastructure uses OPGW fiber optic cables installed on power transmission lines, providing high resilience and availability. This modernization includes the creation of 85 new Edge Data Centers. These units will bring the company’s total to 255 Edge Data Centers nationwide to support low-latency applications.

To further optimize this network, the project is based on Reconfigurable Optical Add-Drop Multiplexer (ROADM) technology and a flexible optical grid, embedded in Nokia solutions. These technologies optimize long-haul transport, expand revenue opportunities by handling traffic growth more dynamically, and reinforce high-demand routes with compact, energy-efficient equipment.

ROADM functions as an "intelligent traffic system," enabling remote reconfiguration, new route activation, and traffic rerouting—accelerating service turn-up, reducing response times, and increasing overall service stability. With the flexible optical grid, Eletronet can transport more data over the same fiber, enabling these ultra-high speeds without new fiber installations, ensuring scalability for future demand and large strategic projects.

NEC and Nokia will continue delivering robust optical network solutions to support Eletronet’s growth, driving broader and faster internet coverage across Brazil. By enabling scalable, high-performance connectivity, both companies aim to foster digital transformation and AI-driven innovation, contributing to economic development and a more connected society for the future.

"We are living in a moment of rapidly growing data traffic, driven by cloud applications, intensive use of Artificial Intelligence, and the continuous increase in connected devices. This scenario demands increasingly robust networks to keep pace with the digital economy. The modernization of our backbone directly addresses this need, ensuring that Internet Service Providers (ISPs), telecom operators and submarine cable operators, data centers, and hyperscalers have an infrastructure ready to support the country’s growth."
- Rogério Garchet, CEO, Eletronet

"Advancing our backbone is essential to support Eletronet’s next expansion cycles and the delivery of high-quality services. Leveraging the experience of Nokia and NEC in this project strengthens our continuous evolution strategy and ensures the levels of quality, security, and performance our customers require."
- Emerson Hioki, Chief Technology Officer (CTO), Eletronet"

This is a highly relevant project for Brazil. With Nokia’s solutions, Eletronet is reinforcing the infrastructure needed to support growing demand across market segments for low-latency connectivity, increased capacity, and distributed processing. At the same time, it expands broadband connectivity options and access to digital services across different regions of the country. We value Eletronet’s trust in Nokia and NEC’s partnership with us on this initiative."
- Rafael Mezzasalma, Nokia Director for Brazil"

NEC is delighted to support Eletronet’s business expansion in collaboration with Nokia. Leveraging decades of optical networking expertise built on our Global Center of Excellence, we are committed to building a robust optical foundation worldwide that fuels business growth and delivers positive social impact."
- Masayuki Kayahara, Corporate SVP, Global Network Division, NEC Corporation

Technical Information, Multimedia, and Related News
Website: Nokia Optical Networks
Website: Nokia 1830 PSS
Website: Nokia 1830 Global Express
Website: NEC Network Transformation Service for Value Added Solutions

About NEC

The NEC Group leverages technology to create social value and promote a more sustainable world where everyone has the chance to reach their full potential. NEC Corporation was established in 1899. Today, the NEC Group’s approximately 110,000 employees utilize world-leading AI, security, and communications technologies to solve the most pressing needs of customers and society.

For more information, please visit https://www.nec.com, and follow us on LinkedIn and YouTube.

TOKYO, Japan, Feb 25, 2026 - (JCN Newswire) - NTT DOCOMO, INC. and Keio University Haptics Research Center announced today that they have successfully conducted a demonstration of high-precision remote robot operation over commercial 5G. By combining Configured Grant,*1 a low-latency network slicing technology,*2 with Keio's Real Haptics® technology,*3 delicate force feedback and tactile sensations were transmitted stably. This marks the world's first demonstration*4 of Configured Grant enabling practical robot teleoperation over commercial 5G.

In the experiment, Configured Grant was applied to the radio link between the terminal and base station to minimize latency and jitter. Results confirmed that latency requirements for practical teleoperation of Real Haptics robots were met, while force reproducibility and operability were improved.

To convey precise force feedback when a remote robot interacts with objects controlled by an operator at a distant location, mobile data communication must maintain low latency and minimal jitter. High or fluctuating latency can disrupt synchronization between the operator and remote robot. This compromises the precise force reproduction of Real Haptics, hindering delicate robot operation.

DOCOMO and Keio University have previously collaborated on the development and testing of Real Haptics for robot teleoperation over mobile networks.*5 By reducing the impact of latency in the wireless segment, highly precise and delicate remote robot control can now be performed stably even under network congestion.

Going forward, the two organizations will continue developing and testing technologies to accelerate the practical use of advanced robot teleoperation.

This demonstration will be exhibited at the NTT Group's booth during MWC Barcelona 2026, organized by GSMA and held in Barcelona, Spain, from March 2 to March 5, 2026.

*1 A scheduling method in which the base station pre-allocates communication resources to specific devices.
*2 A network slicing technology that provides virtualized network segments optimized for low latency.
*3 A technology invented by Professor Kohei Onishi (Keio University Haptics Research Center) that transmits tactile and contact information bidirectionally and reproduces human force on robots.
*4 As of February 25, 2026, according to DOCOMO's research.
*5 NTT DOCOMO, “Evolution of robotics with Force & Tactile Tele-Transmission“ (Japanese only)

Real Haptics® is a registered trademark of MotionLib Inc.

About NTT DOCOMO

NTT DOCOMO, Japan's leading mobile operator with over 91 million subscribers, is one of the global leaders in 3G, 4G and 5G mobile network technologies.Under the slogan “Bridging Worlds for Wonder & Happiness,“ DOCOMO is actively collaborating with global partners to expand its business scope from mobile services to comprehensive solutions, aiming to deliver unsurpassed value and drive innovation in technology and communications, ultimately to support positive change and advancement in global society. https://www.docomo.ne.jp/english/

About Keio University Global Research Institute Haptics Research Center

The Haptics Research Center is aiming to make RealHaptics technology widely and universally available to consumers and companies worldwide and operates a council for RealHaptics technology in which private companies also participate. As a research institution for RealHaptics technology, Keio University holds a core set of related patents. Furthermore, the Haptics Research Center works closely with companies to carry out joint research to explore new applications for the technology. https://haptics-c.keio.ac.jp/

Appendix

Overview of the Demonstration

1. Background

Real Haptics® is a technology that reproduces the force sensation of touching objects on a robot. Using Real Haptics, a remote operator can perform delicate tasks by controlling a robot with precise force. By synchronizing the position, force, and speed between the operator robot (the “leader“) and the remote robot (the “follower“) in real time, the system conveys the sensation of touch to the operator and transfers subtle force to the target object.

Applying advanced robots like Real Haptics over mobile data networks enables outdoor operation and expands potential use cases. However, latency and jitters in mobile networks make stable robot teleoperation challenging. In Real Haptics, network delays can hinder force feedback, cause jerky movements, and reduce operational precision.

DOCOMO and Keio University have been exploring various approaches, developing and verifying technologies to reduce the impact of latency and jitters on wireless robot teleoperation. Previously, the two organizations demonstrated the effectiveness of combining network functions that stabilize latency with robot functions that mitigate its negative effects. For this demonstration, it focused on the wireless segment, which has a strong influence on mobile network latency, and introduced Configured Grant, a new approach that directly reduces latency and jitters.

2. Overview of Configured Grant

Configured Grant, a low-latency network slicing technique, assigns dedicated communication resources in advance to specific devices under a base station. This helps minimize latency and jitters in the wireless segment, regardless of network congestion.

Normally, mobile devices communicate with a base station using the Dynamic Grant method (see Figure 1, left). When a device has data to transmit, it first requests communication resources from the base station. The base station then allocates resources based on the status of other devices and notifies the requesting device. The devices then use these resources to transmit the data. The time between the resource request and actual data transmission is known as scheduling delay. This delay always occurs under Dynamic Grant and can fluctuate depending on network conditions, posing a major challenge for stable remote operation of advanced robots, especially in congested networks.

On the other hand, with Configured Grant (see Figure 1, right), the base station pre-allocates exclusive communication resources to a device (or a line) for a specific period. The device can transmit data without requesting resources, effectively eliminating scheduling delay. As a result, both latency and jitters are reduced, enabling more stable wireless remote operation.

Figure 1: Overview of Data Communication Between Device and Base Station

Configured Grant provides a stable mobile network with consistently low latency, ideal for precise teleoperation of advanced robots, regardless of network conditions.

3. Network Configuration and Experimental Method

The demonstration used DOCOMO's commercial 5G SA network, connecting the operator robot (Leader) and remote robot (Follower) via a virtual server on docomo MEC®*1 running the Bilateral Edge Platform™,*2 a proprietary platform currently under development for robot control (Figure 2). Control data packets sent from one robot travel through the uplink via DOCOMO's commercial network and docomo MEC private network to the server. The server then forwards these packets to the other robot over the downlink. Real-time bidirectional packet exchange enables force feedback of Real Haptics control. Furthermore, to simulate realistic teleoperation conditions where video transmission traffic would be present, 20 Mbps of background traffic was added alongside the control traffic.

Configured Grant was implemented at both the base stations and 5G devices. When communication occurs over a line assigned Configured Grant settings, the mechanism becomes active, enabling low-latency transmission.

Figure 2: Experimental Configuration

For the experiment, a hand-type follower and its leader were used to perform a standardized task: grasping a hard wooden block, quickly moving the hand while varying applied force, and transporting it within a set time. The task was performed twice, once using 5G SA with Configured Grant and once using standard 5G SA without it, to compare performance (Figure 3).

Figure 3: Robot Operation

4. Results

Using 5G SA with Configured Grant, both the average communication latency and jitters (standard deviation) were lower compared to standard 5G SA without Configured Grant, meeting the latency requirements for practical teleoperation of Real Haptics robots. Furthermore, as latency characteristics improved, performance metrics for robot operation were also enhanced. The force-feedback reproduction rate*3 increased by 40% (24 points) with Configured Grant, providing more precise force feedback (Figure 4). The smoothness of robot operation, measured by Dimensionless Jerk Cost,*4 decreased by 59%, enabling smoother, more stable control (Figure 5).

Figure 4: Force Feedback Reproduction Results

Figure 5: Robot Motion Smoothness Results

*1 A cloud service providing Multi-access Edge Computing (MEC) features for the 5G era, including low latency and high security.
*2 A platform service that combines ultra-low-latency mobile data communication with remote control and AI operation of force- and touch-sensitive robots.
*3 A measurement of how accurately one robot replicates the force applied to the other robot. Values closer to 100% indicate higher fidelity.
*4 An indicator of motion smoothness based on acceleration changes. Lower values indicate smoother robot movements.

docomo MEC is a registered trademark of NTT DOCOMO, INC.
docomo MEC is provided by NTT DOCOMO, INC. and related services are consigned to and sold by NTT DOCOMO BUSINESS, INC. as the agent.
Bilateral Edge Platform is a trademark of NTT DOCOMO, INC.

TOKYO, Japan Feb 25, 2026 - (JCN Newswire) - NTT DOCOMO, INC. announced today the start of commercial use of an agentic AI system in mobile network operations. The platform went live across the company's mobile network services on February 4, 2026.

Mobile networks are critical social infrastructure, supporting not only daily life and business activities but also public services and communications during disasters. Today's networks have become increasingly complex due to services across 4G and 5G, as well as multi-domain and multi-vendor environments. As a result, faster response times and swift service restoration have become increasingly important for maintenance operations in the event of network failures.

Previously, failures with established procedures were handled through automated, preconfigured processes. However, complex failures without predefined solutions have required multiple engineers to manually collect and analyze large volumes of data to identify root causes, often resulting in longer service restoration times. To address this challenge, DOCOMO developed an agentic AI platform built with AWS's managed services, enabling AI to perform network behavior analysis, troubleshooting and remediation recommendations.

DOCOMO's agentic AI platform is built on Amazon Bedrock AgentCore, which enables the secure governance and deployment of agentic AI at scale, along with high-performance databases for time-series, tabular, and graph data optimized for agentic AI workloads. Orchestrating multiple AI agents and leveraging graph-modeled network topology, the platform analyzes traffic and alarm data in real time from more than one million network devices, including base stations and core network equipment. It detects anomalies, identifies suspected failure points, and presents recommended actions to maintenance engineers.

Using one of the world's largest datasets of its kind, the platform isolates failures, reduces response time for complex network failures that previously required manual analysis by more than 50%, significantly shortening service disruption time and contributing to greater network reliability.

Takahiro Makiyama, General Manager, Network Service Management Department, Network Division, NTT DOCOMO, INC., commented: 

“This initiative represents a major step toward realizing the Autonomous Network operations that DOCOMO aims to achieve.

By adopting agentic AI in maintenance operations, DOCOMO is advancing the automation of network fault response and striving to further reduce service impact for our customers.

By building agentic AI based on data from more than one million network devices on an unprecedented scale, we were able to accelerate development and implementation by utilizing AWS's agentic AI platform and managed database services.

As we move ahead, DOCOMO will continue to advance the use of AI to deliver more comfortable and higher-quality communication services to our customers.“

“DOCOMO's commercialization of the agentic AI system for network operation is a pioneering initiative that underpins stable mobile communication services,“ said Mikihiko Tsunematsu, Director, Telecom, Media, Entertainment, Game & Sports, Strategic Business Unit at Amazon Web Services Japan. “By combining the advanced agent capabilities of Amazon Bedrock AgentCore with the world's largest-scale telecommunications data, the company has successfully built the agentic AI system that can significantly reduce response time to complex network failures. This achievement demonstrates how collaboration between DOCOMO and AWS is making autonomous and intelligent network operations a reality-essential capabilities for 6G and beyond. We are delighted to support DOCOMO as they establish new standards in network reliability and operational efficiency.“

The agentic AI system will be exhibited at the NTT Group's booth during MWC Barcelona 2026, organized by GSMA and held in Barcelona, Spain, from March 2 to March 5, 2026.

Going forward, DOCOMO will continue to pursue advanced AI-driven operations and strive to further enhance service quality for its customers.

About NTT DOCOMO

NTT DOCOMO, Japan's leading mobile operator with over 91 million subscribers, is one of the global leaders in 3G, 4G and 5G mobile network technologies.
Under the slogan “Bridging Worlds for Wonder & Happiness,” DOCOMO is actively collaborating with global partners to expand its business scope from mobile services to comprehensive solutions, aiming to deliver unsurpassed value and drive innovation in technology and communications, ultimately to support positive change and advancement in global society.
https://www.docomo.ne.jp/english/

TOKYO, Feb 24, 2026 - (JCN Newswire) - Mitsubishi Heavy Industries, Ltd. (MHI) today announced the launch of DIAVAULT, a newly developed industrial grade edge data center(1) brand.

DIAVAULT is a digital infrastructure solution that enables on-site data and AI utilization in an on-premises environment (2). It achieves high security and low latency that are difficult to realize in cloud environments. In addition, it is equipped with a stable power supply and cooling systems, enabling long-term stable operation. DIAVAULT will be a key driver accelerating digital transformation in the industrial sector.

Background

With the widespread adoption of IoT and AI, industries increasingly require the ability to process large volumes of data in real time. However, cloud-centric processing faces challenges such as latency and data confidentiality risks. Therefore, the importance of edge computing, which enables fast and distributed processing near devices generating vast amounts of data and the users of this data, is increasing.

In response to these challenges, MHI is promoting the development of on-premises digital infrastructure. DIAVAULT, centered on a high-security edge data center that simultaneously achieves high on-site information processing and stable operation, flexibly covers customer needs from small-scale to inference data centers (3) of several megawatts. It provides a range of edge solutions such as inference environments in manufacturing sites, research facilities, defense-related fields, and 5G connectivity to meet low latency demands.

Key Features

Recently, MHI opened a demonstration AI data center on the premises of Yokohama Hardtech Hub (YHH) established at Mitsubishi Heavy Industries Yokohama Works and started validation of various use cases. This data center has the following features:

1. Servers equipped with the next-generation GPU specialized for AI processing are efficiently cooled by two-phase direct chip cooling (4), achieving powerful computing performance and low PUE (5) with excellent cooling performance.
2. The server room is compact, equivalent to two 20-foot containers, but offers a spacious area for the maintenance of large-depth servers and the CDU (6). It is equipped with an uninterruptible power supply with continuous power feed.
3. Proprietary digital integrated air conditioning control technology optimizes air conditioning and heat sources while monitoring server load, delivering energy-saving effects throughout the year.
4. In addition to robust entry/exit security with two-factor authentication, the entire facility is remotely monitored, enabling stable unmanned operation.

Future Outlook

Building on comprehensive engineering capabilities developed in social infrastructure and data center power, cooling, and digital technologies, MHI is advancing solutions with high resilience and high security to support next-generation generative AI and physical AI. With the deployment of DIAVAULT, MHI will promote the widespread adoption and co-creation of more advanced and reliable AI infrastructure through collaboration with domestic and international partners.

(1) A small-scale data center installed close to users and devices.

(2) A system in which servers are placed at facilities such as company offices, factories, or research institutes to directly manage and process data, rather than using the cloud.

(3) A data center optimized for fast and efficient inference after AI models have been "trained." Equipped with AI accelerators specialized for AI processing.

(4) A cooling technology that circulates an electrically insulating two-phase refrigerant (liquid and gas) through a cold plate on semiconductor chips (processors) inside the server, removing heat without using water.

(5) Power Usage Effectiveness (PUE) is an indicator of how efficiently a data center uses power. The closer to 1.0, the greater the efficiency.

(6) CDU (Coolant Distribution Unit) is a device that circulates, distributes, and adjusts the temperature of coolant to efficiently cool IT equipment such as servers.

The Edge Data Center "DIAVAULT" in YHH

About MHI Group

Mitsubishi Heavy Industries (MHI) Group is one of the world’s leading industrial groups, spanning energy, smart infrastructure, industrial machinery, aerospace and defense. MHI Group combines cutting-edge technology with deep experience to deliver innovative, integrated solutions that help to realize a carbon neutral world, improve the quality of life and ensure a safer world. For more information, please visit www.mhi.com or follow our insights and stories on spectra.mhi.com

KAWASAKI, Japan, Feb 13, 2026 - (JCN Newswire) - Fujitsu and 1Finity (a Fujitsu company) today announced their joint participation in MWC Barcelona 2026.

Under the theme "Intelligence in Motion," Fujitsu and 1Finity will showcase cutting-edge AI solutions for service providers and enterprises and the latest network solutions supporting the AI era.

Fujitsu will share its latest portfolio of AI and computing technologies, including next-generation material development integrating AI, HPC, and quantum computing, agentic AI (a core technology of the Fujitsu Kozuchi AI platform), and FUJITSU-MONAKA (1), Fujitsu’s nextgeneration processor designed for high performance and energy efficiency. 1Finity will highlight its latest portfolio of open, AI-networking solutions that help optimize performance and operations, lower TCO and increase energy efficiency, as well as interactive use case demonstrations.

MWC Barcelona 2026

Fujitsu and 1Finity Booth: 2G60 (Hall 2)

• Date: March 2 (Mon.), to March 5 (Thurs.), 2026
• Venue: Fira Gran Via, Av. Joan Carles I, 64 08908 L'Hospitalet de Llobregat, Barcelona, Spain

Exhibition highlights

1.Technology area

Quantum computing

• Perform complex property evaluations for materials development through the fusion of AI, HPC, and quantum computing.
• Demonstrate the feasibility of comprehensive exploration in the field of catalyst discovery, where conventional property evaluation through experimentation traditionally required enormous time and cost.

FUJITSU-MONAKA

• An Arm-based, next-generation processor utilizing 2nm technology for high power efficiency and performance in AI inference and network processing
• Accelerating green IT infrastructure for AI through collaborations with NVIDIA and Arrcus (planned release 2027)

Multi-AI agent collaboration technology

• Optimizes multi-enterprise supply chains and enhances procurement using multi-AI agent collaboration technology
• Features the Fujitsu secure inter-agent gateway to ensure safe information sharing among AI agents from various vendors

Field support agent

• AI agents that provide on-site support, streamlining service desk operations, especially for network companies
• Interactive demo available

Amalgamation AI

• Rapidly builds AI applications using minimal training data and limited GPU resources
• Enables users without AI expertise to select optimal VLMs for tasks like image recognition, significantly boosting on-site productivity (e.g., factory monitoring).

2. Godzilla experience area

Visitors of the booth can further dive into an immersive experience by becoming one of Japan’s most iconic monsters, Godzilla (2). Guests will step in front of a green screen and, for 30 seconds, mimic the fabled creature's movements. Utilizing Fujitsu's real-time, high-precision skeletal recognition AI which quantifies human movement as data, visitors’ actions will be translated into the monster's impact on a digital cityscape. This technology is part of the AI Technologies and Solutions offering from Uvance, Fujitsu’s business model to address business challenges and solve societal issues.

This experience highlights AI-RAN, a crucial 1Finity technology for disaster preparedness. It demonstrates AI-RAN use cases such as optimizing GPU resources between RAN functions and AI applications during emergencies, and delivering timely warnings to mobile devices, embodying Fujitsu and 1Finity’s vision for a safer, more sustainable society.

3. 1Finity area

AI-ready infrastructure

Open RAN

• 1Finity radios are being deployed by Tier 1 MNOs in multiple use cases, including Massive MIMO for full-scale, high-capacity urban areas.

Open Transport

• High-performance, sustainable and scalable transport solutions for edge/access, metro, long-haul networking and next-generation data centers

Arrcus

• Network solutions centered around Arrcus’ common network operating system, ArcOS, which operates uniformly across diverse platforms from edge to cloud, supporting AI infrastructure with traffic optimization, automation, and scalability

Network optimization

AI operations 

• Multidomain, multivendor AIOps solutions for improving network efficiency, performance and Quality of Experience

Network Modernization

• 1Finity’s multivendor Network Modernization service supports migration to newer technology, optimizing resource utilization, and right-sizing resources to meet changing demands

AI-Driven Opportunities

AI-RAN

• The new Enterprise full-stack AI-RAN solution, including GPUs from NVIDIA, backed by a vibrant partner ecosystem with applications that can be deployed within weeks, enables new business cases and near-term revenue opportunities

Private Wireless

• An all-in-one Private Wireless CBRS solution that enables smart applications for manufacturing, warehousing, military and other use cases

1. FUJITSU-MONAKA:
This new technology applied to FUJITSU-MONAKA is based on results obtained from a project subsidized by the New Energy and Industrial Technology Development Organization (NEDO).
2. Godzilla:
TM ＆ © TOHO CO., LTD.

About Fujitsu

Fujitsu’s purpose is to make the world more sustainable by building trust in society through innovation. As the digital transformation partner of choice for customers around the globe, our 113,000 employees work to resolve some of the greatest challenges facing humanity. Our range of services and solutions draw on five key technologies: AI, Computing, Networks, Data & Security, and Converging Technologies, which we bring together to deliver sustainability transformation. Fujitsu Limited (TSE:6702) reported consolidated revenues of 3.6 trillion yen (US$23 billion) for the fiscal year ended March 31, 2025 and remains the top digital services company in Japan by market share. Find out more: https://global.fujitsu/en-global

About 1Finity

1Finity, a Fujitsu company, is a global provider of communications networks for our connected world. We uniquely combine technological leadership and expertise in open optical and wireless networking, network automation, and applied AI/ML to design, build, operate, and maintain critical digital communications network infrastructure. Collaborating closely with ecosystem partners, we deliver transformative outcomes for service providers and network operators, and enable them to lower TCO, improve network performance, and increase energy efficiency. www.1Finity.com

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