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Nexthink Partners with Softcat

Nexthink announced a new strategic partnership with Softcat to support enterprise clients in enhancing their digital workplace for employees. 

Softcat’s new Go-to-Market strategy offers enterprise customers the ability to enhance the employee experience to boost productivity and collaboration without sacrificing security.

As part of this partnership, Softcat customers now have access to the full suite of Nexthink products including Nexthink Infinity, which offers unparalleled visibility into issue detection, diagnosis & remediation across all endpoints, as well as automated remediations, AI-powered diagnostics, and low code workflow orchestration.

“Nexthink are a key partner in our Enhanced User Experience offering for our enterprise customers, enabling our joint customers access to market leading tools and solutions that dramatically improve their user experience and return on technology investments.” Kelly Calver, Head of Workspace at Softcat.

Additionally, Softcat is set to join Nexthink’s customer advisory board for Europe, providing insight and guidance as Nexthink looks to further expand its product and service offerings.

“We’re honored and excited to be working exclusively with Softcat on this enterprise-level offering,” said Steve Webster, UK&I Sales Director, Nexthink. “By working with a small, select group of vendors, Softcat are providing desperately needed clarity for enterprises on how they can enhance their digital workspace to reduce employee frustration, improve productivity, and increase innovation.”

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Nexthink Partners with Softcat

Nexthink announced a new strategic partnership with Softcat to support enterprise clients in enhancing their digital workplace for employees. 

Softcat’s new Go-to-Market strategy offers enterprise customers the ability to enhance the employee experience to boost productivity and collaboration without sacrificing security.

As part of this partnership, Softcat customers now have access to the full suite of Nexthink products including Nexthink Infinity, which offers unparalleled visibility into issue detection, diagnosis & remediation across all endpoints, as well as automated remediations, AI-powered diagnostics, and low code workflow orchestration.

“Nexthink are a key partner in our Enhanced User Experience offering for our enterprise customers, enabling our joint customers access to market leading tools and solutions that dramatically improve their user experience and return on technology investments.” Kelly Calver, Head of Workspace at Softcat.

Additionally, Softcat is set to join Nexthink’s customer advisory board for Europe, providing insight and guidance as Nexthink looks to further expand its product and service offerings.

“We’re honored and excited to be working exclusively with Softcat on this enterprise-level offering,” said Steve Webster, UK&I Sales Director, Nexthink. “By working with a small, select group of vendors, Softcat are providing desperately needed clarity for enterprises on how they can enhance their digital workspace to reduce employee frustration, improve productivity, and increase innovation.”

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80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

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Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

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