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EasyVista 2024.1 Released

EasyVista launched new product updates – the first in a series of major software enhancements for 2024.

Previous features and updates for 2023 included XLA, AIOps with short-term and threshold predictions, a WhatsApp integration, new PowerBI reports, advanced user forecasting, and much more.

Michael Cohen, Chief Technology Officer at EasyVista noted, “Our latest release is designed to introduce I&O teams to a better way to triage technical issues and speed up downtime for ITSM products, while also enhancing the UI for a more inclusive approach.”

The 2024.1 product release from EasyVista includes digital accessibility, automated IT asset discovery, and enhanced AI capabilities updates. EV Discovery’s Discovery & Dependency Mapping (DDM) roadmap will help customers gain a 360-degree view of their IT landscape; automate asset and configuration management; track changes and maintain audit trails; and seamlessly integrate with EasyVista’s ITSM products—increasing collaboration and operational efficiency. EV Discovery V1 brings IT asset discovery and begins introducing dependency mapping, with additional dependency mapping features slated to roll out later in 2024.

Additionally, EV Pepper AI, the AI layer of the EasyVista platform, will provide realistic value for specific use cases to customers. One such example are Pepper AI automations, out-of-the-box AI-enabled automations that are embedded directly into various features, fields, and workflows to solve specific problems. For instance, AI case summarization is leveraged to suggest a title for the subject field of an incident. In later versions, Pepper AI will provide additional infused AI capabilities across Observe, Reach, and future products.

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EasyVista 2024.1 Released

EasyVista launched new product updates – the first in a series of major software enhancements for 2024.

Previous features and updates for 2023 included XLA, AIOps with short-term and threshold predictions, a WhatsApp integration, new PowerBI reports, advanced user forecasting, and much more.

Michael Cohen, Chief Technology Officer at EasyVista noted, “Our latest release is designed to introduce I&O teams to a better way to triage technical issues and speed up downtime for ITSM products, while also enhancing the UI for a more inclusive approach.”

The 2024.1 product release from EasyVista includes digital accessibility, automated IT asset discovery, and enhanced AI capabilities updates. EV Discovery’s Discovery & Dependency Mapping (DDM) roadmap will help customers gain a 360-degree view of their IT landscape; automate asset and configuration management; track changes and maintain audit trails; and seamlessly integrate with EasyVista’s ITSM products—increasing collaboration and operational efficiency. EV Discovery V1 brings IT asset discovery and begins introducing dependency mapping, with additional dependency mapping features slated to roll out later in 2024.

Additionally, EV Pepper AI, the AI layer of the EasyVista platform, will provide realistic value for specific use cases to customers. One such example are Pepper AI automations, out-of-the-box AI-enabled automations that are embedded directly into various features, fields, and workflows to solve specific problems. For instance, AI case summarization is leveraged to suggest a title for the subject field of an incident. In later versions, Pepper AI will provide additional infused AI capabilities across Observe, Reach, and future products.

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The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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