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Hitachi Digital Services Launches HARC Agents

Hitachi Digital Services unveiled Hitachi Application Reliability Center Agents (HARC Agents), the company’s enterprise platform for trusted Agentic AI. 

The platform combines a full lifecycle of AI services – from concepting to deployment to optimization – to give customers a jump start on mission-critical innovations. A definitive demonstration of advanced automation and human-AI collaboration, HARC Agents enables Hitachi to equip enterprises with complex, scalable AI systems in 30% less time than typically required – significantly reducing time to value.

HARC Agents is comprised of four primary AI resources:

  • R202.ai: a framework for defining the development and deployment of scalable, enterprise-grade AI workloads in a reliable, responsible, observable, and optimal manner.
  • HARC for AI: the Hitachi Application Reliability Center hosting professional and managed services that operationalize AI systems; ensuring they are always on, reliable, and cost optimized.
  • Agent Library (new): a library of pre-built, interconnected agentic AI agents that jump-start more complex agentic AI solution development as well as maximize those solutions’ outputs.
  • Agent Management System (new): a single dashboard centralizing control of all agentic AI platforms across an enterprise environment; simplifying governance, performance monitoring, and compliance to ensure enterprises can confidently harness the power of AI at scale.

“Simply put, HARC Agents exists to make AI enterprise ready at speed and scale. In today’s unforgiving business environment, only the companies that master AI at full enterprise power will survive and thrive. Generic AI solutions may appear attractive in demonstrations, but they are not built for mission-critical enterprise use and will fail when true pressure is applied,” said Roger Lvin, CEO, Hitachi Digital Services. “Too many technology partners are content to run pilots, chase headlines, and talk theory. Hitachi stands apart by delivering operationalized AI that scales globally, safeguards the enterprise, ensures compliance, mitigates risk, and drives measurable outcomes tied directly to business strategy. The future belongs to those who execute with precision and purpose, and to those who choose partners proven to turn AI into real enterprise value.”

“Imagine investing tens of millions into an AI system designed to manage sensitive operations, only to discover a year later that it is unreliable, unsecure, and not ready for production. Enterprises cannot afford to stake their future on hype or fragile AI. With HARC Agents, we’ve built a foundation for agentic systems that are not only secure and reliable but deeply integrated across IT and OT environments. Our approach ensures enterprise-wide observability and operational readiness from day one – turning innovation into scalable, sustainable impact,” explained Premkumar Balasubramanian, CTO, Hitachi Digital Services.

The new Agent Library is a rich collection of over 200 agents sourced corporate-wide from Hitachi’s group companies, with each company offering distinctive technology competencies. The agents are put to work by Hitachi engineers when developing more complex AI systems. The agents then continue to operate on behalf of the customers when they use those systems. Notably, the agents cross six key domains:

  • Industrial AI (vertical-specific use cases)
  • Operations AI
  • Engineering AI
  • Analytical AI
  • Security AI
  • Cloud AI

The Agent Library will continue to grow as new agents are generated to support internal and external customer project needs.

Simultaneously, Hitachi Digital Services also released today its Agent Management System (AMS). Within the HARC Agents framework, the AMS is a centralized observability and control layer via a single “pane of glass” across a heterogeneous set of agentic platforms such as Copilot Studio, Google Agentspace, Lyzr, Ema, and others. The unified visibility, governance, and lifecycle management of intelligent agents enabled by AMS ultimately ensures secure, scalable, and flexible deployment across enterprise environments.

“Hitachi has long advanced the use of AI across all organizational layers – from executives to frontline engineers – supporting diverse applications such as business risk analysis and predictive maintenance. This is made possible by our decades of experience in building and operating IT systems. The deep domain knowledge embedded in our products and systems is what enables us to successfully deploy Agentic AI. HARC Agents represent a future where AI is not just a tool, but a partner that augments human capabilities and helps solve societal challenges. Through digital innovation, Hitachi is committed to delivering value to everyone and realizing a safe, secure, and sustainable society—a Harmonized Society,” said Jun Abe, Chairman of the Board at Hitachi Digital Services and Executive Vice President of Hitachi, Ltd., General Manager of the Digital Systems & Services Division. 

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Hitachi Digital Services Launches HARC Agents

Hitachi Digital Services unveiled Hitachi Application Reliability Center Agents (HARC Agents), the company’s enterprise platform for trusted Agentic AI. 

The platform combines a full lifecycle of AI services – from concepting to deployment to optimization – to give customers a jump start on mission-critical innovations. A definitive demonstration of advanced automation and human-AI collaboration, HARC Agents enables Hitachi to equip enterprises with complex, scalable AI systems in 30% less time than typically required – significantly reducing time to value.

HARC Agents is comprised of four primary AI resources:

  • R202.ai: a framework for defining the development and deployment of scalable, enterprise-grade AI workloads in a reliable, responsible, observable, and optimal manner.
  • HARC for AI: the Hitachi Application Reliability Center hosting professional and managed services that operationalize AI systems; ensuring they are always on, reliable, and cost optimized.
  • Agent Library (new): a library of pre-built, interconnected agentic AI agents that jump-start more complex agentic AI solution development as well as maximize those solutions’ outputs.
  • Agent Management System (new): a single dashboard centralizing control of all agentic AI platforms across an enterprise environment; simplifying governance, performance monitoring, and compliance to ensure enterprises can confidently harness the power of AI at scale.

“Simply put, HARC Agents exists to make AI enterprise ready at speed and scale. In today’s unforgiving business environment, only the companies that master AI at full enterprise power will survive and thrive. Generic AI solutions may appear attractive in demonstrations, but they are not built for mission-critical enterprise use and will fail when true pressure is applied,” said Roger Lvin, CEO, Hitachi Digital Services. “Too many technology partners are content to run pilots, chase headlines, and talk theory. Hitachi stands apart by delivering operationalized AI that scales globally, safeguards the enterprise, ensures compliance, mitigates risk, and drives measurable outcomes tied directly to business strategy. The future belongs to those who execute with precision and purpose, and to those who choose partners proven to turn AI into real enterprise value.”

“Imagine investing tens of millions into an AI system designed to manage sensitive operations, only to discover a year later that it is unreliable, unsecure, and not ready for production. Enterprises cannot afford to stake their future on hype or fragile AI. With HARC Agents, we’ve built a foundation for agentic systems that are not only secure and reliable but deeply integrated across IT and OT environments. Our approach ensures enterprise-wide observability and operational readiness from day one – turning innovation into scalable, sustainable impact,” explained Premkumar Balasubramanian, CTO, Hitachi Digital Services.

The new Agent Library is a rich collection of over 200 agents sourced corporate-wide from Hitachi’s group companies, with each company offering distinctive technology competencies. The agents are put to work by Hitachi engineers when developing more complex AI systems. The agents then continue to operate on behalf of the customers when they use those systems. Notably, the agents cross six key domains:

  • Industrial AI (vertical-specific use cases)
  • Operations AI
  • Engineering AI
  • Analytical AI
  • Security AI
  • Cloud AI

The Agent Library will continue to grow as new agents are generated to support internal and external customer project needs.

Simultaneously, Hitachi Digital Services also released today its Agent Management System (AMS). Within the HARC Agents framework, the AMS is a centralized observability and control layer via a single “pane of glass” across a heterogeneous set of agentic platforms such as Copilot Studio, Google Agentspace, Lyzr, Ema, and others. The unified visibility, governance, and lifecycle management of intelligent agents enabled by AMS ultimately ensures secure, scalable, and flexible deployment across enterprise environments.

“Hitachi has long advanced the use of AI across all organizational layers – from executives to frontline engineers – supporting diverse applications such as business risk analysis and predictive maintenance. This is made possible by our decades of experience in building and operating IT systems. The deep domain knowledge embedded in our products and systems is what enables us to successfully deploy Agentic AI. HARC Agents represent a future where AI is not just a tool, but a partner that augments human capabilities and helps solve societal challenges. Through digital innovation, Hitachi is committed to delivering value to everyone and realizing a safe, secure, and sustainable society—a Harmonized Society,” said Jun Abe, Chairman of the Board at Hitachi Digital Services and Executive Vice President of Hitachi, Ltd., General Manager of the Digital Systems & Services Division. 

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.