Skip to main content

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 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

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 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...