Cherwell Software and Bomgar, a provider of secure remote support solutions, announced the integration of Cherwell Service Management and Bomgar chat and remote support.
The integration will be included in the Cherwell Service Management 4.6 release, available this summer.
Vance Brown, Cherwell CEO, sees this integration as a logical progression in helping Cherwell customers create better experiences for their own customers. “We’re certain that integrating Bomgar’s chat and remote support capabilities will help Cherwell customers resolve issues more quickly and will dramatically improve the quality of service desk support.”
Cherwell Service Management users can seamlessly harness the full power of the Bomgar platform and initiate secure chat sessions from any of the Cherwell Service Management clients, with full capture of Chat history, file transfers, and session recordings. This rich history can be easily configured to link to any module, such as Incident, Service Request, other out-of-the-box management processes, or any custom module. IT departments can choose what integrations point(s) they desire to use for the Bomgar integration.
The integration enables end-users and service desk technicians to initiate Bomgar remote support sessions with one click from anywhere in the Cherwell self-service portal or rich client. Help desk/service desk technicians can provide secure, web-based chat and remote support for any server, computer, tablet, or Apple, Android, and BlackBerry mobile device, in real time—no matter where it’s located or what operating system the customer is using. Once the session is completed, the Chat transcript and any related items, such as file transfers or a link to a session recording, are saved.
“Since Cherwell Service Management is so flexible and easily configured, companies are also using it in departments outside of IT, and the Bomgar chat functionality will enhance all of those customer experiences,” said Russ Duffey, Bomgar vice president business development and strategic alliances.
“Imagine being able to chat with HR about benefits or with facilities about a busted pipe or with IT about a broken printer — all from one system. The possibilities are endless,” said Josh Caid, Cherwell product manager.
The Latest
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.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...