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Geeky Gadgets
3 days ago
- Business
- Geeky Gadgets
What Is a Triage AI Agent Automation & Multi-Agent Systems Explained
What if the key to solving complex, high-stakes challenges in industries like healthcare, cybersecurity, or customer service wasn't a human expert, but an intelligent system that never sleeps? Enter the world of triage AI agents, a new evolution in automation that's reshaping how organizations prioritize and manage tasks. Inspired by the life-or-death urgency of medical triage, these systems don't just organize workflows—they make data-driven decisions in real-time, making sure that critical issues are addressed immediately while routine tasks are handled with precision. In a world where delays can cost lives, revenue, or reputations, triage AI agents are proving to be indispensable allies. IBM Technology explores the mechanics and fantastic potential of triage AI agents, revealing how they combine multi-agent systems, large language models (LLMs), and domain-specific knowledge to transform task management. You'll uncover how these systems operate behind the scenes, from collecting and assessing data to routing tasks with unparalleled efficiency. Whether you're curious about their role in reducing patient wait times, thwarting cyber threats, or enhancing customer satisfaction, this deep dive will illuminate why triage AI agents are more than just another automation tool—they're a glimpse into the future of intelligent decision-making. Could this be the breakthrough your industry has been waiting for? Triage AI Agents Overview How Triage AI Agents Work Triage AI agents streamline workflows by automating the intake, assessment, and routing of tasks. This structured process is composed of three primary components: Intake Agent: This component collects data from users or systems through conversational interfaces or APIs. It connects to knowledge sources such as historical records, templates, or client-specific data to ensure the information gathered is both accurate and relevant. This component collects data from users or systems through conversational interfaces or APIs. It connects to knowledge sources such as historical records, templates, or client-specific data to ensure the information gathered is both accurate and relevant. Assessment Agent: Once data is collected, this agent evaluates the information using domain-specific knowledge, search APIs, or LLMs. It identifies the task's nature, diagnoses potential issues, and determines the most appropriate course of action. Once data is collected, this agent evaluates the information using domain-specific knowledge, search APIs, or LLMs. It identifies the task's nature, diagnoses potential issues, and determines the most appropriate course of action. Routing Agent: In the final step, the task is either executed or directed to the appropriate resource. This is achieved through automation tools, communication platforms, or priority management systems. By integrating these components, triage AI agents reduce delays, optimize task management, and enhance overall operational efficiency. Their ability to handle complex workflows with minimal human intervention makes them a valuable asset for organizations aiming to improve productivity. The Evolution of Triage: From Medicine to AI The concept of triage has its roots in military medicine, where patients were prioritized based on the urgency of their conditions rather than their rank or status. This principle of prioritization has since been adopted across various industries where efficient task management is critical. In the digital age, AI agents have taken this concept to new heights by replicating and enhancing human decision-making through automation and artificial intelligence. These systems are designed to handle the growing complexity of modern workflows, offering precision and speed that surpass traditional methods. By automating the triage process, organizations can allocate resources more effectively, making sure that critical tasks receive immediate attention while routine tasks are managed systematically. What are Triage AI Agents? Watch this video on YouTube. Below are more guides on AI agents from our extensive range of articles. Applications Across Key Industries Triage AI agents are versatile tools with applications that span multiple sectors. Their ability to intelligently prioritize and manage tasks is transforming key industries in the following ways: Healthcare: Triage AI agents streamline patient intake processes, assess symptoms, and route cases to the appropriate medical professionals. This reduces wait times, enhances diagnostic accuracy, and improves overall patient care. Triage AI agents streamline patient intake processes, assess symptoms, and route cases to the appropriate medical professionals. This reduces wait times, enhances diagnostic accuracy, and improves overall patient care. Cybersecurity: These agents analyze potential threats, prioritize vulnerabilities, and direct incidents to the appropriate teams. By automating these processes, organizations can bolster their security posture and respond to threats more effectively. These agents analyze potential threats, prioritize vulnerabilities, and direct incidents to the appropriate teams. By automating these processes, organizations can bolster their security posture and respond to threats more effectively. Customer Service: In customer service, triage AI agents automate the prioritization of inquiries, making sure that urgent issues are addressed promptly while routine queries are resolved efficiently. This improves customer satisfaction and reduces response times. The adaptability of triage AI agents makes them suitable for any domain requiring intelligent task management. Their ability to integrate seamlessly with existing systems further enhances their utility across diverse applications. Technologies Powering Triage AI Agents The effectiveness of triage AI agents is underpinned by a combination of advanced technologies and tools. These technologies work in tandem to create intelligent, adaptable, and efficient AI solutions: Large Language Models (LLMs): Models like GPT enable triage AI agents to process and interpret natural language, enhancing their ability to assess and prioritize tasks accurately. Models like GPT enable triage AI agents to process and interpret natural language, enhancing their ability to assess and prioritize tasks accurately. Domain-Specific Knowledge: By incorporating industry-specific data, these agents make informed decisions that are tailored to the context of each task. By incorporating industry-specific data, these agents make informed decisions that are tailored to the context of each task. Search APIs: These tools allow agents to access and analyze external data sources, making sure comprehensive evaluations and informed decision-making. These tools allow agents to access and analyze external data sources, making sure comprehensive evaluations and informed decision-making. Frameworks: Platforms such as Langflow, Langchain, and Crew AI provide developers with the resources needed to build and customize triage AI systems, allowing them to meet specific organizational needs. These technologies collectively empower triage AI agents to deliver consistent and reliable performance across a variety of use cases. Why Triage AI Agents Matter The adoption of triage AI agents offers several significant benefits that address common challenges in modern workflows: Speed: By automating the prioritization and routing of tasks, these systems minimize delays and improve response times, making sure that critical issues are addressed without unnecessary lag. By automating the prioritization and routing of tasks, these systems minimize delays and improve response times, making sure that critical issues are addressed without unnecessary lag. Consistency: Automated decision-making eliminates human biases, making sure uniform and objective task prioritization across all operations. Automated decision-making eliminates human biases, making sure uniform and objective task prioritization across all operations. Scalability: Triage AI agents can handle increasing volumes of tasks without compromising performance, making them ideal for organizations experiencing growth or managing high workloads. By addressing these challenges, triage AI agents enhance operational efficiency and deliver measurable improvements across industries. Their ability to adapt to evolving demands ensures their long-term relevance and value. The Future of Triage AI Agents As digital transformation continues to accelerate, triage AI agents are poised to become an integral part of workflow automation. Their ability to integrate seamlessly with existing systems and adapt to changing requirements ensures their utility across a wide range of applications. In the future, these agents are expected to play an even more critical role in intelligent decision-making, helping organizations navigate complex challenges with greater ease. By using advancements in artificial intelligence and automation, triage AI agents will continue to redefine task management, offering scalable, consistent, and efficient solutions to meet the demands of an increasingly complex world. Media Credit: IBM Technology Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Forbes
16-05-2025
- Business
- Forbes
From Tactical To Transformational: How Agentic AI Elevates Enterprise IT
The following responses from Art Hu and Sonu Nayyar have been edited for clarity. Hu: Enterprise IT is being asked to deliver greater impact with fewer resources, faster timelines and tighter alignment to business strategy — all while navigating increasingly complex systems. Agentic AI refers to systems designed to act autonomously within defined parameters, observing their environment, making decisions and taking action to achieve specific outcomes, all under enterprise oversight. At Lenovo, we see this as a shift from managing workflows to managing intent. These systems help IT teams move from reactive support to proactive impact, enabling greater scale and responsiveness across the enterprise while freeing people to focus on higher value work. Nayyar: Agentic AI represents a significant evolution, positioning IT as a central orchestrator of enterprise intelligence. Our role now includes architecting secure, scalable and compliant platforms that enable teams across the company to rapidly build, deploy and manage intelligent agents securely and responsibly. This shift places IT at the heart of a future shaped by intelligent, autonomous enterprise systems. As enterprises face growing complexity and pressure to move faster, agentic AI offers a timely catalyst for agility and scale. Hu: It's a meaningful change. Instead of scripting every process, you define the outcome, and the system determines how best to achieve it. That allows IT to contribute directly to strategic goals rather than getting stuck in tactical execution. At Lenovo, we're using this model to improve how we manage infrastructure and user experience — with systems that optimize performance based on business context, not just static rules. Nayyar: Agentic AI is shifting the primary focus of enterprise IT away from managing individual tasks and toward orchestrating intelligent, goal-driven outcomes. Unlike traditional automation, which executes fixed workflows, agentic AI enables intelligent systems to reason over intent, evaluate multiple paths and dynamically adapt to achieve strategic outcomes. For instance, rather than simply restarting a failed service, an IT agent can investigate the root cause by correlating logs, recent deployments and telemetry data — and then decide whether to roll back a change, alert a team or initiate a fix, all while adhering to service-level agreements. Similarly, an agent tasked to reduce cloud cost by 15 percent can explore options like reallocating workloads, right-sizing instances or pausing idle resources, choosing the most effective route in real time. These agents operate within enterprise-defined policies, providing autonomy while preserving governance. With this ability to independently pursue objectives, agentic AI is transforming IT from a reactive support function into a strategic driver of business value. Nayyar: We're seeing agentic systems contribute meaningfully in areas far beyond routine tasks. Their capabilities now extend into deep research, strategic planning and contextual reasoning — positioning them as true brainstorming partners and problem-solving assistants. By augmenting human creativity and accelerating complex decision-making, these agents are helping teams innovate faster and more effectively. Hu: That's been our experience as well. For example, in our Premier Support contact centers, we've introduced generative AI tools that assist agents during customer interactions, translating across languages, summarizing case histories and recommending next steps. These tools are designed to support — not replace — our teams, allowing them to deliver faster, more effective service. And for enterprises looking to build similar capabilities, we've made a growing set of AI assets available through the Lenovo AI Library — a curated collection of models and use-cases that help teams accelerate responsible AI deployment. Hu: Agentic AI helps us act faster and with more precision. When disruptions occur, these systems can assess what's happening, trigger remediation workflows and escalate them when necessary — all while keeping human teams informed. It's not about removing control, but about reducing delay. This proactive posture helps minimize impact and protect business continuity. Nayyar: Agentic AI doesn't just react — it enables enterprises to proactively detect, assess and respond to real-time disruptions with agility. Whether it's identifying unusual network behavior that may indicate a cyberthreat, rerouting resources during a supply chain disruption, or helping discover and evaluate contingency plans during supply chain disruptions, agentic systems can continuously monitor signals, reason over multiple data streams and recommend actions — all within the boundaries of enterprise policies. In critical domains like cybersecurity and operational resilience, final decisions are always informed by human-defined policies and priorities. This collaborative approach augments human capabilities with critical insights, driving faster, more informed decisions — all with essential oversight that ensures resilience and adaptability. Nayyar: Agentic AI empowers enterprises to accelerate innovation, deliver more personalized experiences and optimize operational efficiency. However, this transformative power necessitates a parallel commitment to ethical and responsible AI. At NVIDIA, we prioritize explainable, auditable and enterprise-governed solutions that build trust with our customers, regulators and our workforce. This commitment is reflected in how we design, test and deploy our agentic systems across the enterprise. Hu: Trust is key to sustainable AI adoption. At Lenovo, we've built responsible AI practices into our systems — from design to deployment. Our Product Diversity Office plays a role in evaluating inclusivity and accessibility, which is vital as these systems begin to touch more parts of the business. And we're also focused on talent, helping our teams build the skills to manage and lead with AI, not just use it. As these tools evolve, so do the roles around them. Our goal is to ensure that people stay at the center of innovation, supported — not replaced — by technology.
Zawya
15-05-2025
- Business
- Zawya
NTT DATA unveils Smart AI AgentTM Ecosystem, revolutionizing industry solutions with intelligent automation and strategic alliances
Agentic ecosystem and services portfolio support clients end-to-end, from advisory to agent management Patented plug-in solution transforms RPA bots into intelligent agents NTT DATA to establish an OpenAI Center of Excellence to accelerate the development and deployment of Smart AI Agents. Dubai, UAE – NTT DATA, a global leader in digital business and technology services, today announced a comprehensive enterprise-grade Smart AI AgentTM Ecosystem with industry-specific solutions to help clients transform their business. The company also announced a patented plug-in solution that turns legacy bots into autonomous intelligent agents, and an expanded key alliance network for providing best-fit solutions. "The rapid evolution of AI presents both immense opportunities and challenges for businesses," said Yutaka Sasaki, President and Chief Executive Officer, NTT DATA Group. "At NTT DATA, we have developed the comprehensive capabilities needed to guide our clients through these transformative times and empower them to shape their future with the power of AI." Assured outcome solutions with embedded Smart AI Agent NTT DATA has deployed hundreds of Smart AI Agent instances in support of sophisticated processes and decision-making at clients. The company's roadmap encompasses a continuous stream of new agents to support more complex use cases from a range of industries as well as shared functions. For example: Healthcare: Current agents are autonomously classifying, prioritizing and summarizing insurance appeals and making decisions about medical necessity among other responsibilities. The near-term roadmap includes agents that specialize in early interventions, medication compliance, payer validation, and preventing fraud, waste and abuse. Automotive manufacturing: Agents already are analyzing regulatory warning letters and citations. The company is now developing agents that specialize in root-cause analysis of defects; initiate corrective actions, recalls or fixes; and launch compliance reviews as needed. Finance: Agentic AI solutions are assisting banks, partners and consumers in the continuous pursuit of client and engagement validation requirements, including Know Your Customer and other fraud detection and anti-crime capabilities, minimizing transaction and payment vulnerability. Supply chain and logistics: Agents are helping clients select and securely do business with AI startup partners, while also building AI agent prototypes to help businesses deploy and integrate pilots with purchasing workflows and processes, and monitoring adoption, performance and return on investment. Next up are domain-specific steps including agents that intelligently manage procurement services. Marketing: In one of many examples, a multi-agent system integrates with a hyperscaler platform to autonomously analyze and categorize user profiles and build psychographic profiles for hyper-personalized ad recommendations. This system continuously learns and adapts, delivering boosted sales and revenue to clients in many industries. Based on the company's comprehensive approach to agentic AI, NTT DATA can offer assured outcomes that help clients heighten performance, improve security and cyber resilience, and ignite innovation for profitable growth and superior stakeholder experiences. 'Agentic AI is the next transformative wave that will impact every sector, far more than what we have seen with Generative AI so far,' said Abhijit Dubey, CEO of NTT DATA, Inc. 'It's not just about boosting creativity or productivity. It's about unlocking new capabilities that can take initiative, make decisions and collaborate with humans in entirely new ways. With our deep expertise in responsible innovation, trailblazing alliances, and visionary clients, we're excited to lead this future — building the foundation for a reimagined human-machine hybrid workplace and a bold new business landscape.' Comprehensive Smart AI Agent Ecosystem guides clients through AI adoption NTT DATA's Smart AI Agent Ecosystem builds on previous developments to scale the breadth and agility of composable agentic AI solutioning. Key components include: Managed agentic services that help clients build, adopt, manage and scale transformative solutions. Solutions with embedded Smart AI Agents that offer assured outcomes for clients, including solutions for specific industries and horizontal functions. Additional Smart AI Agents targeting industry and horizontal needs. Smart AI Agent platform that incorporates integrated tools, utilities, accelerators and best practices; and access to a marketplace with additional agents, large language models (LLMs) and small language models (SLMs). AI-ready infrastructure backed by services that leverage public cloud, private cloud, network and cybersecurity. Alliances with world-leading technology providers and world-class startups. Responsible by design including security, governance and compliance. The expanded ecosystem empowers clients to envision new ways of operating with smarter automation, resolve global skills shortages and maximize return on investments. Clients also benefit from the assurance of working with a trusted, full-service provider with global scale, scope and expertise. The Smart AI Agent Ecosystem is complemented by an array of proven NTT DATA services including structured readiness and risk assessments, managed services tailored to hyperscaler AI offerings, and multi-agent management services in hybrid vendor environments. Every aspect of the ecosystem is grounded in the company's commitment to responsible AI – ensuring it is trustworthy, ethical and secure by design. 'We've been leveraging NTT DATA's end-to-end Agentic AI Services for Hyperscaler AI Technologies to explore both pro-code and low-code agentic AI experiences,' said Pankaj Shah, VP, Chief Information and Digital Officer, Hyster-Yale Materials Handling, Inc. 'With their step-by-step advisory approach and outcome-focused strategy, we're now exploring powerful multi-agent models and identifying new use cases to align with our business objectives and to reimagine how we operate.' Industry-leading a lliances and partnerships offer deep choice NTT DATA recently announced a strategic collaboration agreement with OpenAI to drive innovation in generative AI. As part of this agreement, NTT DATA will establish an OpenAI CoE (Center of Excellence) to accelerate the development and deployment of new generative AI services powered by the OpenAI APIs. These services will be tailored to specific industries and business functions, and will be introduced globally to deliver enhanced value to clients. In addition to formal collaborations with world-leading technology providers, NTT DATA also has established alliances with world-class innovative startups including, for example: Rafay Systems: Rafay's platform supports NTT DATA's delivery of a scalable, secure and developer-friendly Platform-as-a-Service experience on top of AI infrastructure (GPU PaaS), enabling enterprises to streamline GenAI adoption, reduce operational complexity and accelerate the deployment of production-grade AI workloads. The enterprise-grade Agent Platform integrates LLMs to enhance NTT DATA's Digital Workplace Services. This GenAI-powered automation enables NTT DATA to enhance Service Desk operations, reduce costs and deliver personalized context-aware support to various clients. Agentic AI services portfolio meets clients where they are with end-to-end ecosystem The company's previously announced Agentic AI Services for Hyperscaler AI Technologies offers a comprehensive suite of cloud-managed services to help organizations harness the full potential of agentic AI by leveraging hyperscaler AI technologies. NTT DATA is rapidly scaling their Agentic AI Services for Hyperscaler AI Technologies to deliver greater value as organizations increasingly mature on agentic AI and adopt multi-AI agent models. For example, leveraging Azure AI Agent Service on Azure AI Foundry, NTT DATA can build, manage and orchestrate multi-agent workflows across multiple platforms. This approach simplifies complex multi-agent deployments. Additionally, NTT DATA is helping clients work across the agentic AI spectrum by making its tooling available across clients' cloud platforms. This means that any agent NTT DATA builds can easily be transferred to a clients' cloud environment across Microsoft Azure, AWS and Google Cloud Platform. Patented solution transforms bots into autonomous intelligent agents NTT DATA also announced a patented solution that transforms legacy bots into intelligent agent assets. This plug-in capability is especially important to companies that want to adopt AI but are constrained by technological debt. Millions of Robotic Process Automation (RPA) bots have been deployed by businesses worldwide for rules-based automation. Similar to a plug-in module that turns a basic television into a smart TV, NTT DATA's new solution can transform bots into intelligent agents that operate autonomously while complying with governance and policies for security and privacy. 'AI is causing a massive shift similar to the early days of the internet — reshaping how we work, solve problems and create value,' Dubey said. 'We're not just watching this future unfold — we're driving it. At NTT DATA, we're delivering clients real, measurable impact from AI solutions already, and this patented, transformative plug-in is just one more proof point of what's possible when innovation meets execution.' Visit our website for more information about NTT DATA's Smart AI Agent Ecosystem. To learn about additional case studies, please read 'A Force for Good: How AI and GenAI are reshaping our world.' About NTT DATA NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long-term success. As a Global Top Employer, we have experts in more than 50 countries and a robust partner ecosystem of established and startup companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future.
National Post
15-05-2025
- Business
- National Post
NTT DATA Unveils Smart AI Agent™ Ecosystem, Revolutionizing Industry Solutions with Intelligent Automation and Strategic Alliances
Article content Smart AI Agent™ offers industry-specific solutions with assured outcomes Agentic ecosystem and services portfolio support clients end-to-end, from advisory to agent management Patented plug-in solution transforms RPA bots into intelligent agents NTT DATA to establish an OpenAI Center of Excellence to accelerate the development and deployment of Smart AI Agents. Article content Article content TOKYO & LONDON — NTT DATA, a global leader in digital business and technology services, today announced a comprehensive enterprise-grade Smart AI Agent™ Ecosystem with industry-specific solutions to help clients transform their business. The company also announced a patented plug-in solution that turns legacy bots into autonomous intelligent agents, and an expanded key alliance network for providing best-fit solutions. Article content 'The rapid evolution of AI presents both immense opportunities and challenges for businesses,' said Yutaka Sasaki, President and Chief Executive Officer, NTT DATA Group. 'At NTT DATA, we have developed the comprehensive capabilities needed to guide our clients through these transformative times and empower them to shape their future with the power of AI.' Article content NTT DATA has deployed hundreds of Smart AI Agent instances in support of sophisticated processes and decision-making at clients. The company's roadmap encompasses a continuous stream of new agents to support more complex use cases from a range of industries as well as shared functions. For example: Article content Healthcare: Current agents are autonomously classifying, prioritizing and summarizing insurance appeals and making decisions about medical necessity among other responsibilities. The near-term roadmap includes agents that specialize in early interventions, medication compliance, payer validation, and preventing fraud, waste and abuse. Automotive manufacturing: Agents already are analyzing regulatory warning letters and citations. The company is now developing agents that specialize in root-cause analysis of defects; initiate corrective actions, recalls or fixes; and launch compliance reviews as needed. Finance: Agentic AI solutions are assisting banks, partners and consumers in the continuous pursuit of client and engagement validation requirements, including Know Your Customer and other fraud detection and anti-crime capabilities, minimizing transaction and payment vulnerability. Supply chain and logistics: Agents are helping clients select and securely do business with AI startup partners, while also building AI agent prototypes to help businesses deploy and integrate pilots with purchasing workflows and processes, and monitoring adoption, performance and return on investment. Next up are domain-specific steps including agents that intelligently manage procurement services. Marketing: In one of many examples, a multi-agent system integrates with a hyperscaler platform to autonomously analyze and categorize user profiles and build psychographic profiles for hyper-personalized ad recommendations. This system continuously learns and adapts, delivering boosted sales and revenue to clients in many industries. Article content Based on the company's comprehensive approach to agentic AI, NTT DATA can offer assured outcomes that help clients heighten performance, improve security and cyber resilience, and ignite innovation for profitable growth and superior stakeholder experiences. Article content 'Agentic AI is the next transformative wave that will impact every sector, far more than what we have seen with Generative AI so far,' said Abhijit Dubey, CEO of NTT DATA, Inc. 'It's not just about boosting creativity or productivity. It's about unlocking new capabilities that can take initiative, make decisions and collaborate with humans in entirely new ways. With our deep expertise in responsible innovation, trailblazing alliances, and visionary clients, we're excited to lead this future — building the foundation for a reimagined human-machine hybrid workplace and a bold new business landscape.' Article content NTT DATA's Smart AI Agent Ecosystem builds on previous developments to scale the breadth and agility of composable agentic AI solutioning. Key components include: Article content Managed agentic services that help clients build, adopt, manage and scale transformative solutions. Solutions with embedded Smart AI Agents that offer assured outcomes for clients, including solutions for specific industries and horizontal functions. Additional Smart AI Agents targeting industry and horizontal needs. Smart AI Agent platform that incorporates integrated tools, utilities, accelerators and best practices; and access to a marketplace with additional agents, large language models (LLMs) and small language models (SLMs). AI-ready infrastructure backed by services that leverage public cloud, private cloud, network and cybersecurity. Alliances with world-leading technology providers and world-class startups. Responsible by design including security, governance and compliance. Article content The expanded ecosystem empowers clients to envision new ways of operating with smarter automation, resolve global skills shortages and maximize return on investments. Clients also benefit from the assurance of working with a trusted, full-service provider with global scale, scope and expertise. Article content The Smart AI Agent Ecosystem is complemented by an array of proven NTT DATA services including structured readiness and risk assessments, managed services tailored to hyperscaler AI offerings, and multi-agent management services in hybrid vendor environments. Every aspect of the ecosystem is grounded in the company's commitment to responsible AI – ensuring it is trustworthy, ethical and secure by design. Article content 'We've been leveraging NTT DATA's end-to-end Agentic AI Services for Hyperscaler AI Technologies to explore both pro-code and low-code agentic AI experiences,' said Pankaj Shah, VP, Chief Information and Digital Officer, Hyster-Yale Materials Handling, Inc. 'With their step-by-step advisory approach and outcome-focused strategy, we're now exploring powerful multi-agent models and identifying new use cases to align with our business objectives and to reimagine how we operate.' Article content NTT DATA recently announced a strategic collaboration agreement with OpenAI to drive innovation in generative AI. As part of this agreement, NTT DATA will establish an OpenAI CoE (Center of Excellence) to accelerate the development and deployment of new generative AI services powered by the OpenAI APIs. These services will be tailored to specific industries and business functions, and will be introduced globally to deliver enhanced value to clients. Article content In addition to formal collaborations with world-leading technology providers, NTT DATA also has established alliances with world-class innovative startups including, for example: Article content Rafay Systems: Rafay's platform supports NTT DATA's delivery of a scalable, secure and developer-friendly Platform-as-a-Service experience on top of AI infrastructure (GPU PaaS), enabling enterprises to streamline GenAI adoption, reduce operational complexity and accelerate the deployment of production-grade AI workloads. The enterprise-grade Agent Platform integrates LLMs to enhance NTT DATA's Digital Workplace Services. This GenAI-powered automation enables NTT DATA to enhance Service Desk operations, reduce costs and deliver personalized context-aware support to various clients. Article content The company's previously announced Agentic AI Services for Hyperscaler AI Technologies offers a comprehensive suite of cloud-managed services to help organizations harness the full potential of agentic AI by leveraging hyperscaler AI technologies. Article content NTT DATA is rapidly scaling their Agentic AI Services for Hyperscaler AI Technologies to deliver greater value as organizations increasingly mature on agentic AI and adopt multi-AI agent models. For example, leveraging Azure AI Agent Service on Azure AI Foundry, NTT DATA can build, manage and orchestrate multi-agent workflows across multiple platforms. This approach simplifies complex multi-agent deployments. Article content Additionally, NTT DATA is helping clients work across the agentic AI spectrum by making its tooling available across clients' cloud platforms. This means that any agent NTT DATA builds can easily be transferred to a clients' cloud environment across Microsoft Azure, AWS and Google Cloud Platform. Article content NTT DATA also announced a patented solution that transforms legacy bots into intelligent agent assets. This plug-in capability is especially important to companies that want to adopt AI but are constrained by technological debt. Millions of Robotic Process Automation (RPA) bots have been deployed by businesses worldwide for rules-based automation. Similar to a plug-in module that turns a basic television into a smart TV, NTT DATA's new solution can transform bots into intelligent agents that operate autonomously while complying with governance and policies for security and privacy. Article content 'AI is causing a massive shift similar to the early days of the internet — reshaping how we work, solve problems and create value,' Dubey said. 'We're not just watching this future unfold — we're driving it. At NTT DATA, we're delivering clients real, measurable impact from AI solutions already, and this patented, transformative plug-in is just one more proof point of what's possible when innovation meets execution.' Article content Visit our website for more information about NTT DATA's Smart AI Agent Ecosystem. To learn about additional case studies, please read ' A Force for Good: How AI and GenAI are reshaping our world.' Article content Article content Article content Article content Article content Contacts Article content Media Contacts NTT DATA, Inc. Article content Article content Article content
Tahawul Tech
10-05-2025
- Business
- Tahawul Tech
NVIDIA and ServiceNow on a mission to reimagine employee productivity as they launch new reasoning model
ServiceNow and NVIDIA announced an expansion of their partnership to fuel a new class of intelligent AI agents across the enterprise. This includes the debut of a new high-performance ServiceNow reasoning model, Apriel Nemotron 15B— developed in partnership with NVIDIA—that evaluates relationships, applies rules, and weighs goals to reach conclusions or make decisions. The open-source LLM is post-trained with NVIDIA and ServiceNow-provided data, helping deliver lower latency, lower inference costs, and faster agentic AI. The companies also unveiled plans to bring accelerated data processing to ServiceNow Workflow Data Fabric with the integration of select NVIDIA NeMo microservices, driving a closed-loop data flywheel process that enhances model accuracy and personalized user experiences. The Apriel Nemotron 15B reasoning model represents a significant step forward in developing compact, enterprise-grade LLMs purpose-built for real-time workflow execution. The model was trained using NVIDIA NeMo, the NVIDIA Llama Nemotron Post-Training Dataset, and ServiceNow domain-specific data with NVIDIA DGX Cloud on Amazon Web Services (AWS). It delivers advanced reasoning capabilities in a smaller size—making it faster, more efficient, and cost effective to run on NVIDIA GPU infrastructure as an NVIDIA NIM microservice. Benchmarks show promising results for the model's size category, reinforcing its potential to power agentic AI workflows at scale. The debut of this model comes as enterprise AI continues to rise as a transformative force—helping businesses address growing complexity, navigate macroeconomic uncertainty, and drive smarter, more resilient operations. To support ongoing model innovation and AI agent performance, ServiceNow and NVIDIA also unveiled a new collaboration on a joint data flywheel architecture that will integrate ServiceNow Workflow Data Fabric and select NVIDIA NeMo microservices. This integrated approach curates and contextualizes enterprise workflow data to refine and optimize reasoning models, with guardrails in place to help ensure that customers are in control of how their data is used and processed in a secure and compliant manner. This enables a closed-loop learning process that improves model accuracy and adaptability—accelerating the development and deployment of highly personalized, context-aware AI agents designed to enhance enterprise productivity. 'With this new Apriel Nemotron 15B reasoning model, we're powering intelligent AI agents that can make context-aware decisions, adapt to complex workflows, and deliver personalized outcomes at scale,' said Jon Sigler, EVP of Platform and AI at ServiceNow. 'But the model is just one part of the innovation. Our collaboration building a data flywheel—powered by Workflow Data Fabric and NVIDIA NeMo—enables a virtuous cycle of learning and improvement. This helps us build AI agents that are contextually aware, deeply personalized, and aligned to the real-time needs of the enterprise.' 'NVIDIA and ServiceNow share a mission to reimagine employee productivity through AI tools that help people get more done,' said Kari Briski, Vice President of Generative AI Software for Enterprise at NVIDIA. 'Together, we've built the Apriel Nemotron 15B model to serve as an enterprise-grade reasoning engine and plan to integrate NVIDIA NeMo microservices into ServiceNow Workflow Data Fabric, providing a powerful foundation for intelligent digital agents.' The new Apriel Nemotron 15B reasoning model and data flywheel integration will better equip AI agents to meet the growing demands of customers with continuous data and process feedback. For example, imagine an AI agent resolving a complex billing issue by pulling in past customer interactions, reasoning through the problem, and recommending the next best step—getting faster, more accurate, and more efficient with every case it handles. Together, ServiceNow and NVIDIA are turning enterprise data into real-time, personalized action. This latest milestone builds on the recently announced AI agent evaluation tools and integration of NVIDIA Llama Nemotron models with the ServiceNow AI Platform to accelerate agentic AI development. ServiceNow and NVIDIA have a shared vision of designing innovations that ensure LLMs—and the experiences they're powering—are not only intelligent, but also measurable, secure, and ready for real-world deployment. The co-development of the Apriel Nemotron 15B reasoning model and data flywheel integration marks a natural next step in the companies' deep partnership—furthering their collaboration to power enterprise workflows with greater speed, precision, and cost-efficiency. Availability – The Apriel Nemotron 15B model is expected to be available in Q2 2025.
