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Digitate Advances Agentic AI Platform

Digitate announced the launch of its latest release designed to help IT and business leaders materialize their vision of autonomous enterprise and ticketless operations. 

Built on ignio™ – an Agentic AI platform for IT and business operations, the new release introduces a suite of AI agents capable of handling even the most complex IT and business tasks with speed and precision, supercharging employee productivity and elevating business resiliency to new heights.  

“The complexity of today’s enterprises needs intelligent agents that can understand, decide, and act with autonomy,” said Rahul Kelkar, Chief Product Officer of Digitate. “With ignio, we envisioned a future of autonomous enterprises and pioneered the fusion of AI and automation from our very first release 10 years ago. Each subsequent release has empowered our customers to move away from reactive IT and step confidently into a world of proactive, self-driving ticketless operations. Our new Agentic AI platform and AI agents mark the next phase in this evolution, empowering CIOs, SRE teams, IT and business operations to harness the power of ignio’s agentic platform and AI agents to accelerate their autonomous enterprise journey.”

Digitate’s Agentic AI framework reimagines enterprise AI as a system of autonomous, goal-oriented, and context-aware agents. These agents operate independently or collaboratively, continuously learning from their environment, understanding intent, and making informed decisions — elevating enterprise IT from rule-based automation to intelligent autonomy.

Digitate’s initial AI agents will address the following specific IT functions and personas:  

  • AI Agent for IT Event Management: Designed to autonomously ingest, correlate, and prioritize millions of IT events in real time, this agent cuts through noise, identifies patterns, and flags actionable insights—transforming event chaos into clear operational intelligence.
  • AI Agent for Incident Resolution: Built to intelligently resolve incidents across hybrid environments, this agent combines contextual understanding with autonomous execution. It handles known issues and adapt to emerging ones—significantly reducing mean time to resolution (MTTR).
  • AI Agent for SRE: Tailored for Site Reliability Engineering (SRE) teams, this agent enhances observability and tracking across the enterprise tech stack, enabling hands-on support and proactive reliability management.
  • AI Assist for CIO: Engineered for CIOs who require unified, high-level data from across the enterprise to make informed decisions about strategy, governance, business continuity, and cost optimization. 

Digitate will offer early previews of the new AI agents, with general availability to follow in the coming weeks.  

The AI agent for IT event management is now available for a free trial. 

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Digitate Advances Agentic AI Platform

Digitate announced the launch of its latest release designed to help IT and business leaders materialize their vision of autonomous enterprise and ticketless operations. 

Built on ignio™ – an Agentic AI platform for IT and business operations, the new release introduces a suite of AI agents capable of handling even the most complex IT and business tasks with speed and precision, supercharging employee productivity and elevating business resiliency to new heights.  

“The complexity of today’s enterprises needs intelligent agents that can understand, decide, and act with autonomy,” said Rahul Kelkar, Chief Product Officer of Digitate. “With ignio, we envisioned a future of autonomous enterprises and pioneered the fusion of AI and automation from our very first release 10 years ago. Each subsequent release has empowered our customers to move away from reactive IT and step confidently into a world of proactive, self-driving ticketless operations. Our new Agentic AI platform and AI agents mark the next phase in this evolution, empowering CIOs, SRE teams, IT and business operations to harness the power of ignio’s agentic platform and AI agents to accelerate their autonomous enterprise journey.”

Digitate’s Agentic AI framework reimagines enterprise AI as a system of autonomous, goal-oriented, and context-aware agents. These agents operate independently or collaboratively, continuously learning from their environment, understanding intent, and making informed decisions — elevating enterprise IT from rule-based automation to intelligent autonomy.

Digitate’s initial AI agents will address the following specific IT functions and personas:  

  • AI Agent for IT Event Management: Designed to autonomously ingest, correlate, and prioritize millions of IT events in real time, this agent cuts through noise, identifies patterns, and flags actionable insights—transforming event chaos into clear operational intelligence.
  • AI Agent for Incident Resolution: Built to intelligently resolve incidents across hybrid environments, this agent combines contextual understanding with autonomous execution. It handles known issues and adapt to emerging ones—significantly reducing mean time to resolution (MTTR).
  • AI Agent for SRE: Tailored for Site Reliability Engineering (SRE) teams, this agent enhances observability and tracking across the enterprise tech stack, enabling hands-on support and proactive reliability management.
  • AI Assist for CIO: Engineered for CIOs who require unified, high-level data from across the enterprise to make informed decisions about strategy, governance, business continuity, and cost optimization. 

Digitate will offer early previews of the new AI agents, with general availability to follow in the coming weeks.  

The AI agent for IT event management is now available for a free trial. 

The Latest

For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...