ManageEngine announced the launch of its revamped user interface for ServiceDesk Plus On-Demand, the SaaS version of the company’s ITIL-ready help desk software.
The revamped UI includes a number of features designed to increase productivity and simplify help desk operations, including multi-level nested business rules, keyboard short cuts and Facebook-style notifications. Continuing the disruption created with the free Standard Edition, ServiceDesk Plus On-Demand now follows a non-linear, multi-tier pricing model that ensures flexible, affordable adoption of a SaaS-based help desk.
Today's help desk industry faces new challenges due to rapidly evolving technologies, which threaten to reduce help desk speed, productivity and usability. When IT technicians first start working with a help desk application, they often spend more time getting acquainted with the tool than addressing the needs of their end users. This reduces productivity and, in turn, end-user satisfaction. To address these challenges, the revamped ServiceDesk Plus On-Demand UI promises IT technicians increased productivity and, most important, very simple and easy-to-use operation.
"We live in a technology age where software user experience boundaries are pushed very hard," said Rajesh Ganesan, director of product management, ManageEngine. "Service desk agents live by the service desk tool all day and expect the user experience to match that of consumer applications. We understand this and are committed to continually providing our customers the best user experience across all device types and form factors."
Bridging the gap between the real needs of a customer and the perceived needs of a product developer is no small task. Therefore, the UI has been extensively fine-tuned to incorporate customer feedback and suggestions to deliver true value. Moreover, the UI is built on the latest JavaScript charting libraries and a customized JavaScript framework to provide the best user experience possible. The resulting UI is simple, intuitive and fast. As observed during its testing stage, the new UI delivered a 5x increase in productivity due to improved loading times of the thread and detailed view of requests. In turn, technicians can resolve tickets faster and, ultimately, increase end-user satisfaction.
The new UI features provide users an experience that is:
- Fast: Faster page loads save valuable time, and quick keyboard shortcuts let users log incidents from anywhere within the tool.
- Focused: Single window operation with minimal pop-ups keeps users focused on the task at hand.
- Instant: Immediate, Facebook-like notifications keep support representatives informed and on top of their tickets.
- Simple: Simplified topic management for solutions creates and maintains a strong knowledge base. Instant search of help desk configurations and multi-level nested business rules enable hassle-free help desk configurations.
- Clear: Time-lined, color-coded conversations with end users account for better interaction.
The revamped UI is an automatic upgrade available immediately, free of cost to all existing and new ServiceDesk Plus On-Demand customers. Typical linear pricing has been modified to have multiple price tiers based on number of technicians and asset combinations, delivering more flexibility in choosing the right subscription model. The free Standard Edition of ServiceDesk Plus On-Demand offers IT help desk operations with no restrictions on request and technician count. The Professional and Enterprise editions - along with valuable add-ons - offer a complete, ITIL-compliant help desk experience.
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.