Nexthink launched Nexthink Infinity.
The entirely cloud-based platform brings unparalleled visibility and analytics across any environment so that IT teams can become proactive and provide an always-on workplace to their employees, everywhere.
Leveraging powerful machine learning and benchmarking, the Infinity platform enables IT teams to diagnose any issue, automatically determine the root cause and then remediate millions of devices. The platform offers endless integration capabilities because of its unique, proprietary architecture; providing IT teams with data ingestion capabilities from any application – including critical collaboration apps such as Zoom or Teams – to track degradation across any device: physical, virtual, or mobile.
“The last two years have been truly transformative for IT teams in the enterprise – balancing the acceleration of remote work with more complex applications to support, combined with rising expectations from employees to have high-quality workplace experiences everywhere,” said Pedro Bados, Co-Founder and CEO at Nexthink. “Infinity is our future – mixing years of experience in digital experience with the most advanced technologies in ML, data processing and visualization to provide digital workplace teams unparallel levels of visibility, diagnostic and automation.”
Key highlights of the new Infinity platform include:
- Infinite Scalability – The new platform scales up to millions of workplaces, thousands of SaaS and local applications, and billions of telemetry data-points accessible to IT teams in seconds via APIs, Nexthink Query Language (NQL) or our visual editors.
- Diagnostics & Analytics – AI-driven incident diagnostics speed up troubleshooting by spotting patterns, comparing to benchmarks, and then attributing issues to root causes, allowing IT teams to become truly proactive.
- The new Experience Central – Nexthink’s patented “Moments of Experience” algorithm and digital experience scores provide IT leaders with continuous understanding of the key issues that are affecting the digital journey of the employees in the enterprise and impacting productivity.
- Collaboration Experience – By combining application telemetry with advanced machine-learning analytics, IT administrators can rapidly validate, isolate, and remediate on leading Collaboration Apps like
- Teams and Zoom – preventing any performance issues for employees.
- New Alerting module – Built-in and baseline-based alerting system with capabilities to assess the impact of issues and provide prioritization for resolution. A growing collection of built-in alerts from the Nexthink Library allows IT teams to quickly operationalize and customize their system for the most common problems and integrate it with third-party systems for proper handling.
- Advanced Remediation and Integration capabilities – Cloud-intelligence retrieves data and delivers instant fixes on any issue from behind the scenes without interrupting employees. Additionally, the new connector system and APIs native in the new Infinity platform allow out of the box integration with the most popular system management, ITSM and tools for a full automation of IT.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
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 ...