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Infovista Launches TEMS for Industry 4.0

Infovista announced TEMS for Industry 4.0 – a range of new solutions that address the lifecycle needs and challenges of industries as they move towards wider use of connectivity enabled applications and processes.

Built on a core platform trusted by over 1700 wireless network operators globally, TEMS for Industry 4.0 provides an advanced set of tools for network deployment, optimization and operations for connected applications across public and private 3G, LTE and 5G networks.

“The push towards Industry 4.0 is bringing new verticals into the realm of wireless connectivity and with it a need for skills and tools to ensure everything works as expected for a next generation of connected applications,” says Steve Bowker, SVP Global Networks for Infovista.

“TEMS has been trusted by network operators for over 20 years and our Industry 4.0 solution has been designed to help industrial customers design, deploy and scale reliably without performance issues while minimizing business disruption by finding and fixing problems quickly.”

Aimed at a broad spectrum of industrial users including mining, ports, agriculture, transit, safety, rail, transportation and fleet operations; TEMS for Industry 4.0 maximizes the benefits, in terms of reliability, efficiency, total cost of ownership, agility and accuracy to offer true end-to-end wireless connectivity testing and monitoring. The TEMS for Industry 4.0 solution offers a diverse set of elements to meet the needs of different use cases and includes:

- Data Collection Hardware: Probes, phones and custom-designed hardware on which the active test and monitoring software runs are available in different form factors to support various test environments and use cases.

- Data Collection Software Clients: Active test and monitoring software clients that can be embedded to test and monitor connectivity of connected industrial applications.

- Active Testing: Active testing software enabling layer 1 to 7 end-to-end network and application testing, supporting attended and unattended use cases.

- Connectivity Test and Monitoring Orchestration: Centralized platform enabling management, control and real time reporting & analysis of the connectivity testing and monitoring data.

- Connectivity Data Analytics: Insightful Post processing & analysis of collected data using the TEMS products or 3rd party solutions.

- Predictive Connectivity: Analytics and data used to de-risk mission critical application design and increase reliability and performance during operations.

TEMS for Industry 4.0 solutions are in trials with a number of automotive manufacturers, ports and mining companies today and will be generally available July 2020.

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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 ...

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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.

Infovista Launches TEMS for Industry 4.0

Infovista announced TEMS for Industry 4.0 – a range of new solutions that address the lifecycle needs and challenges of industries as they move towards wider use of connectivity enabled applications and processes.

Built on a core platform trusted by over 1700 wireless network operators globally, TEMS for Industry 4.0 provides an advanced set of tools for network deployment, optimization and operations for connected applications across public and private 3G, LTE and 5G networks.

“The push towards Industry 4.0 is bringing new verticals into the realm of wireless connectivity and with it a need for skills and tools to ensure everything works as expected for a next generation of connected applications,” says Steve Bowker, SVP Global Networks for Infovista.

“TEMS has been trusted by network operators for over 20 years and our Industry 4.0 solution has been designed to help industrial customers design, deploy and scale reliably without performance issues while minimizing business disruption by finding and fixing problems quickly.”

Aimed at a broad spectrum of industrial users including mining, ports, agriculture, transit, safety, rail, transportation and fleet operations; TEMS for Industry 4.0 maximizes the benefits, in terms of reliability, efficiency, total cost of ownership, agility and accuracy to offer true end-to-end wireless connectivity testing and monitoring. The TEMS for Industry 4.0 solution offers a diverse set of elements to meet the needs of different use cases and includes:

- Data Collection Hardware: Probes, phones and custom-designed hardware on which the active test and monitoring software runs are available in different form factors to support various test environments and use cases.

- Data Collection Software Clients: Active test and monitoring software clients that can be embedded to test and monitor connectivity of connected industrial applications.

- Active Testing: Active testing software enabling layer 1 to 7 end-to-end network and application testing, supporting attended and unattended use cases.

- Connectivity Test and Monitoring Orchestration: Centralized platform enabling management, control and real time reporting & analysis of the connectivity testing and monitoring data.

- Connectivity Data Analytics: Insightful Post processing & analysis of collected data using the TEMS products or 3rd party solutions.

- Predictive Connectivity: Analytics and data used to de-risk mission critical application design and increase reliability and performance during operations.

TEMS for Industry 4.0 solutions are in trials with a number of automotive manufacturers, ports and mining companies today and will be generally available July 2020.

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.