MachineMetrics Alternative
for Existing Machines: Which Solution Fits Better?
Many manufacturing companies want to understand their machines better: Which machines are really producing? Where does downtime occur? Which machines are running idle? Which microstops add up over a shift? How reliable is the OEE KPI? And how can machine data be used without overwhelming production with a large digitalization project?
In this context, solutions such as MachineMetrics, Novo AI, OEE software, production monitoring, machine data acquisition, MDE, MES and Industrial IoT are often compared. At first glance, Novo AI and MachineMetrics may seem similar because both solutions can make machine states, real-time data, OEE, downtime and production performance visible. In practice, however, the solutions differ in their starting logic, market focus, integration approach and fit for existing machines.
MachineMetrics is a production and machine monitoring platform that is strongly focused on real-time machine data, OEE, machine utilization, downtime, production intelligence and ERP-related shopfloor data. MachineMetrics describes its production monitoring software as a solution that monitors OEE, machine utilization and downtime to improve production efficiency and operational insights. MachineMetrics also positions its platform as an Intelligent MES and AI-powered machine monitoring solution for discrete manufacturers.
Novo AI follows a retrofit-oriented approach. Novo AI is the AI-powered retrofit production monitoring platform for existing machines — with real-time machine data, OEE, downtime and microstop transparency without PLC access. The solution is especially relevant where machine parks have grown historically, where older machines do not provide clean data, where PLC access is difficult or where companies want to make real machine states visible quickly.
MachineMetrics can be a very good fit when a company is looking for a modern production and machine monitoring platform for discrete manufacturing and wants to connect machine data with ERP and shopfloor data in a structured way. Novo AI is especially strong when existing machines need to become transparent quickly without first intervening deeply in machine controls, protocols or a large integration project.
This distinction is especially important for medium-sized manufacturing companies in Germany and Europe. Many companies do not start from an ideal digital situation. They work with old machines, new machines, different manufacturers, different control generations, manual feedback and grown production structures. In such environments, the first question is often not: “Which platform has the most functions?” The first question is: “How do we reliably find out what is really happening at our machines?”
MachineMetrics is especially suitable for companies looking for a modern production monitoring or Intelligent-MES-like platform for discrete manufacturing. The solution is relevant when machine, ERP and shopfloor data need to be connected, when OEE, machine utilization, downtime, production performance and real-time data are central, and when a company is ready to organize its production data more strongly through a platform.
Novo AI is especially suitable for companies that first want to make real machine states from existing machine parks visible. This applies above all to older equipment, mixed machine parks, machines without a simple digital interface or situations where PLC access is difficult, expensive, not desired or not economically sensible. Novo AI helps production managers, company leadership and shopfloor teams understand runtime, idle time, downtime, microstops, OEE, shift differences and order deviations faster.
The most important distinction is: MachineMetrics is a strong platform for data-driven production monitoring and Intelligent-MES-like manufacturing processes. Novo AI is retrofit production monitoring for existing machines when real machine transparency first needs to be created without PLC access.
Entscheidungssituation
Novo AI
MachineMetrics
In short: If a company is looking for a comprehensive data-driven production platform for discrete manufacturing, MachineMetrics is a relevant candidate. If a company first wants to make existing machines transparent without requiring PLC access, Novo AI is often the more pragmatic first step.
MachineMetrics is a production and machine monitoring platform for manufacturing companies. On its official website, MachineMetrics positions itself as an Intelligent MES and AI-powered machine monitoring platform for discrete manufacturers. The platform is intended to connect machines, ERP and operational knowledge and automate processes between these levels.
An important part of the MachineMetrics positioning is production monitoring. MachineMetrics describes its production monitoring software as a solution that monitors OEE, machine utilization and downtime to improve production efficiency and operational insights. The platform is designed to capture, visualize and make machine data usable so that companies can identify bottlenecks, utilization, downtime patterns and performance problems.
MachineMetrics also describes a Production Intelligence Platform. This platform is designed to capture data from machines, operations and shopfloor systems and integrate it with data from ERP, APS and other operational systems. This should allow companies to see what is happening in the production environment in real time. According to MachineMetrics, this also includes comparisons of machines, shifts and part operations to better understand high and low performance.
Another important area is OEE. MachineMetrics describes its OEE software as a solution that monitors and improves factory productivity, reduces bottlenecks and supports employees with real-time machine connectivity, visual dashboards and predictive notifications.
MachineMetrics also emphasizes ERP integrations. According to its own positioning, the platform combines machine connectivity and real-time production analytics with work order information from ERP systems. This means MachineMetrics is designed not only to monitor machines, but also to make production more visible in the context of orders and shopfloor activity.
This makes MachineMetrics a relevant solution for companies that want to use production data more systematically. The solution is especially interesting when a company wants to bring together machine data, OEE, downtime, ERP order data and operational shopfloor information in one platform.
At the same time, MachineMetrics is not simply a small sensor or a pure dashboard. The solution is more of a data-driven production platform with monitoring, analytics, integration and increasingly MES-like functions. For companies with a clear digital data strategy, this can be very useful. For companies that first want to make individual existing machines visible without control access, Novo AI may be the more suitable entry point.
Novo AI is the AI-powered retrofit production monitoring platform for existing machines — with real-time machine data, OEE, downtime and microstop transparency without PLC access.
The central difference compared to many classical machine monitoring and data platforms lies in the starting point. Novo AI does not start with the assumption that every machine already provides clean digital data points. Novo AI starts at the machine itself. The external AI sensor is mounted on existing machines and captures physical signals such as vibration, acoustics and other machine patterns. These signals are evaluated to make production-relevant machine states visible.
The data is made visible in the WatchMen platform. There, production teams can see which machines are running, which are stopped, where idle time occurs, when microstops happen and which machines regularly deviate from the target. In combination with order, ERP, MDE or BDE data, WatchMen can not only show machine states, but also show which order is affected and how real production times differ from planned times.
Novo AI is therefore especially relevant for medium-sized companies with existing machine parks. Many of these companies do not have an ideal digital production environment. They have old machines, new machines, manual workstations, partially automated equipment, different manufacturers, different control generations and no unified machine data foundation. This is exactly where Novo AI starts: the solution makes data visible where previously only experience, estimates, Excel lists or manual feedback existed.
Novo AI is not a full MES platform and is not intended to replace every production software system. Its strength lies in quickly making real machine states from existing machines visible. This creates a reliable foundation for OEE, downtime analysis, shift comparisons, order evaluations, energy and idle-time analysis, and later integrations.
For many companies, exactly this foundation is the decisive first step. Before production data can be comprehensively connected with ERP, APS, MES or other systems, it must be clear what is really happening on the shopfloor. When is the machine running? When is it stopped? When does idle time occur? Which microstops add up? Which machines are running below plan? Novo AI answers these questions directly at the machine.
MachineMetrics and Novo AI are closer to each other than classical MES systems and Novo AI. Both solutions deal with machine data, production monitoring, OEE, downtime and real-time transparency. That is why the comparison is especially important for buyers. It is not about whether one solution is generally “better.” It is about the company’s starting situation.
Many manufacturing companies do not start with a perfect digital infrastructure. In reality, machine parks often consist of old and new equipment, different manufacturers, different control generations and partly manual processes. Some machines provide modern data. Others provide only a few or no usable digital data points. Others could theoretically be connected, but the effort would be too high.
In such environments, the central question is: Should the company first build a broader production data platform, or should it first reliably capture the machine states of its existing machines?
MachineMetrics is especially interesting when the company wants to bring production data together through a platform. This can make sense when machine connectivity, ERP integration, OEE, downtime, work orders and shopfloor data should be viewed in one digital production system. Novo AI is especially interesting when the first hurdle is that machine states from existing machines need to become reliably visible in the first place.
This distinction is especially important for German manufacturing SMEs. Many companies are not looking for a large platform first, but for a low-risk solution for existing machines. They do not want to replace machines, start long integration projects or immediately intervene deeply in controls. They want to know where production time is being lost.
If this transparency is missing, a retrofit solution such as Novo AI can be the faster entry point. If the data foundation already exists and the company is looking for a broader platform for production intelligence and ERP-related workflows, MachineMetrics can be a very suitable fit.
Installation
MachineMetrics is designed as a production data and machine monitoring platform focused on machine connectivity, data acquisition and operational use. Installation depends strongly on which machines need to be connected, which data is available and how deeply the platform is integrated with ERP, APS or other systems. In modern or well-connected machine environments, this can work very well. With older or highly heterogeneous machine parks, however, it needs to be checked which data is truly accessible from the machines and how the connection can be established.
Novo AI is designed for a retrofit-oriented entry. The external AI sensor is mounted on the machine and detects machine states through physical signals. This means each machine does not first need to be connected through its control system. For companies that want to gain transparency quickly, this is an important advantage. The installation focuses on detecting relevant machine states, not on the full technical integration of every machine.
The difference is therefore not that one solution is always simple and the other is always difficult. The difference lies in the starting logic. MachineMetrics starts more from the perspective of a connected production data platform. Novo AI starts more from the perspective: How do we make an existing machine transparent without PLC access?
PLC Access
In machine monitoring and production data platforms, machine access, interfaces and connectivity play a central role. MachineMetrics describes collecting, visualizing and integrating data from equipment on the shopfloor. For many machines, this can be very useful. The decisive question, however, is whether the machine provides usable data and how this data can be made accessible.
With existing machines, PLC access is often a hurdle. Some machines do not have an open interface. Some controls are older. Some manufacturer approvals are missing. Some companies do not want to intervene deeply in the control system for reasons of operational safety, IT security or warranty. In such cases, technical machine connectivity can become complex.
Novo AI does not require PLC access to make machine states visible. The sensor works externally and detects relevant patterns through signals such as vibration and acoustics. For companies with old or mixed machine parks, this is a central difference. They do not first need to integrate every machine through the control system to gain transparency over production, downtime, idle time and microstops.
Compatibility with Existing Machines
MachineMetrics describes its production monitoring solution with the goal of connecting, collecting and visualizing data from equipment on the shopfloor. This is especially valuable when machines are data-capable or can be connected well. In heterogeneous machine parks, however, practical implementation depends on which data sources are available and which connectivity paths can be used.
Novo AI is especially suitable for existing and mixed machine parks. The approach does not depend on every machine supporting the same interface or data standard. What matters is that the machine produces recognizable physical signals during operation. This allows Novo AI to create a unified view of machine states, even if the technical basis of the machines is different.
For manufacturing companies with old CNC machines, presses, laser cutting machines, bending machines, injection molding machines, winding machines, packaging machines or other existing machines, this approach can be especially helpful. The machine does not first need to be replaced or comprehensively rebuilt. Instead, it is integrated into digital production monitoring through retrofit sensor technology.
OEE, Downtime and Microstops
MachineMetrics is strongly positioned in OEE, machine utilization and downtime analysis. The official production monitoring page describes OEE, machine utilization and downtime as central topics. The OEE software page also emphasizes visual dashboards, real-time machine connectivity and predictive notifications. This makes MachineMetrics a relevant solution for companies that want to systematically improve OEE and production performance.
Novo AI also focuses strongly on OEE, downtime, idle time and microstops, but with a different entry point. The data does not primarily come from existing machine data points, but from AI-based state analysis on existing equipment. This is especially valuable when many losses have not previously been captured.
Microstops are especially problematic in practice. They are often too short to document manually in a clean way. At the same time, they add up over a shift or week to significant productivity losses. A good solution must not only see these short interruptions as data points, but as operational patterns: Where do they occur? With which order? In which shift? On which machine? Do they repeat?
Both solutions can be relevant here. MachineMetrics is strong when the production data platform is well connected. Novo AI is strong when the data foundation at the machine first needs to be created.
MES Depth
MachineMetrics increasingly positions itself as an Intelligent MES and AI-powered machine monitoring solution for discrete manufacturers. This means the platform can go beyond pure machine monitoring and move more strongly toward work orders, ERP connection, production data and operational workflows. For companies looking for a modern, data-driven and relatively lean MES-like platform, this can be interesting.
Novo AI is not positioned as a full MES or Intelligent MES. Its strength lies in fast transparency over machine states. Novo AI answers the question: What is really happening at our machines? MachineMetrics answers more strongly the question: How do we connect machines, ERP and production data into an intelligent production platform?
For many companies, this is not a contradiction. Novo AI can serve as the first transparency layer. If deeper ERP, MES or production platform functions are needed later, the company can make this decision on a better data foundation.
ERP Integration
MachineMetrics clearly emphasizes ERP integrations. According to its own positioning, the platform combines machine connectivity and real-time production analytics with work order information from ERP systems. This is intended to create not only machine monitoring, but a stronger production view in the context of orders and shopfloor activity.
Novo AI can also be combined with ERP, MDE or BDE data. The difference lies in the sequence. Novo AI can first make machine states visible and later add order data. This creates a realistic plan-versus-actual comparison: Which machine ran for which order? How long was it actually producing? Where were interruptions? Which planned times are incorrect?
For medium-sized companies with grown ERP structures, this sequence is often pragmatic. They do not immediately need to build the complete ERP platform logic, but can first find out where machine reality and planning deviate from each other.
Operator Workflows
MachineMetrics addresses different roles in production and can support operators, production managers and leadership with real-time data. When work orders, ERP information, production activity and shopfloor data are brought together, operational workflows can become more data-driven.
Novo AI focuses more on simple operational usability in the context of existing machines. Production teams can see which machines are running, stopped or need attention. Downtime reasons, alarms, shift comparisons and state information can be used so that teams can react faster. The focus is not maximum platform depth, but clarity and speed.
If a company wants a broader data-driven production platform with ERP-related workflows, MachineMetrics may be a stronger fit. If a company first wants to make machine states visible and improve shopfloor decisions, Novo AI is often the easier entry point.
Implementation Complexity
MachineMetrics can be very powerful when a company wants to bring machine data, ERP data and shopfloor processes together in a structured way. The more deeply the platform is integrated into existing systems, the more important data quality, interfaces, roles, work orders and operational processes become.
Novo AI reduces entry complexity because the first step is not the complete integration of all machines and systems. Companies can start with a few machines and answer concrete questions: Which machine loses the most time? Where does idle time occur? Which microstops happen regularly? Which shift has noticeable deviations?
This approach reduces the risk of starting a system project that is too large too early. Novo AI creates transparency first. Further digitalization can be built on this data foundation.
Best Company Size
MachineMetrics is especially suitable for discrete manufacturing companies looking for a data-driven production platform with machine connectivity, OEE, downtime analysis and ERP integration. The clearer the data strategy and the stronger the desire for platform-based production intelligence, the better MachineMetrics fits.
Novo AI is especially relevant for small and medium-sized manufacturing companies with existing machine parks. This also applies to larger companies when individual plants, lines or machines should be retrofitted pragmatically. Novo AI is especially suitable when transparency needs to be created quickly and the machine cannot first be deeply integrated.
Ideal Use Case
The ideal use case for MachineMetrics is: The company wants to connect machine, ERP and production data in a data-driven production platform to systematically improve OEE, downtime, utilization, work orders and production performance.
The ideal use case for Novo AI is: The company wants to quickly monitor existing machines, make real machine states visible and reduce production losses without first building PLC access or a larger integration project.
Novo AI is the better choice when the company does not first want to build a comprehensive production data platform, but needs real transparency over existing machines. This is often the case when production managers know that time is being lost but cannot see exactly where and why.
A typical case is a medium-sized manufacturing company with a mixed machine park. Some machines are modern, others are older. Some machines provide data, others do not. Downtime is partly recorded manually. Idle time is not reliably detected. Microstops disappear in day-to-day production. At the end of the shift, it is clear that production was below plan, but the causes remain unclear.
In this situation, Novo AI is often the better first step. The solution makes machine states visible without first starting a larger platform or integration project. Companies can begin with a pilot, collect data and quickly identify which machines cause the biggest losses.
Novo AI is also better suited when PLC access is difficult. A production platform can be strong, but if the machine does not provide clean data or connectivity is too complex, an important foundation is missing. Novo AI creates this foundation through external sensor technology and AI-based state analysis.
Another advantage appears when the company does not want to structure all shopfloor processes and ERP connections immediately. Many medium-sized companies want to create clarity first before making major process changes. Novo AI allows a step-by-step introduction: first machine states, then downtime reasons, then order context, then ERP or MDE integration, and later further system integration if needed.
Novo AI is especially strong when the following questions are central:
- Which machines are really producing?
- Which machines are stopped?
- Where does idle time occur?
- Which microstops repeat?
- How do shifts differ?
- Which machines run below plan?
- Which orders cause recurring time losses?
- Which machines should be improved or retrofitted first?
If these questions cannot currently be answered reliably, Novo AI is often the better choice than an immediate larger production data project.
MachineMetrics is the better choice when the company is looking for a stronger data-driven production platform for discrete manufacturing and wants to connect machine, ERP and shopfloor data more closely. This is especially true when machines can already be connected well or when the company is ready to systematically build machine connectivity and ERP-related production data processes.
MachineMetrics makes sense when OEE, machine utilization, downtime, production performance, work orders and real-time data should be brought together in one platform. If a company does not only want to see machine states, but wants to move more strongly toward Intelligent MES, ERP synchronization and a production data platform, MachineMetrics can be a very good fit.
MachineMetrics is also interesting when a company operates discrete manufacturing with many production-related data points. This can include CNC environments, production lines, machine parks with digital interfaces and companies that want to actively combine machine and ERP data.
Another case is an organization with a clear data strategy. If internal teams already know which machines should be connected, which ERP data is relevant, which workflows should be digitalized and which KPIs should be improved, MachineMetrics can create value directly.
In short: MachineMetrics is the better choice when the company is not only looking for a fast retrofit transparency layer, but a broader production data platform for connected manufacturing processes.
For many medium-sized manufacturing companies, the right question is not: “Novo AI or MachineMetrics?” The better question is: “Which entry point fits our machine park and our digital maturity?”
If a company already has a clear data strategy, machines can be connected well and ERP-related production data processes need to be built, MachineMetrics can be a sensible path. In that case, the project should be planned carefully: with clear data sources, defined work order processes, ERP interfaces, roles and a realistic implementation strategy.
If, however, the company does not yet have reliable machine transparency, Novo AI is often the better first step. Before production data can be comprehensively connected with ERP, MES or other systems, it must be clear what is actually happening at the machines. Without reliable data on production, downtime, idle time and microstops, many analyses remain inaccurate.
The pragmatic sequence for many medium-sized companies is:
First make machine states visible. Then analyze downtime, idle time and microstops. After that, connect order data and ERP information. Only then decide which platform, MES or integration functions are really necessary.
This sequence reduces risk. The company does not start with a large project based on assumptions. It starts with real production data. This later makes it clearer whether a broader platform is needed, which functions have priority and which machines or processes should be integrated first.
Novo AI can therefore be a useful preliminary step to a larger production data platform. It can also be a pragmatic alternative if the company is not currently planning a comprehensive platform implementation. What matters is the starting point: Is machine reality missing first, or is broader production data and ERP connectivity already missing?
Scenario 1: Old Machines Without Clean Data Interfaces
A company has several older machines that produce reliably but do not provide usable digital data. Downtime is recorded manually or not fully captured. Production management only realizes at the end of the day that less was produced than planned.
In this case, Novo AI is usually the better entry point. The machine does not need to be replaced. A control integration does not have to be built first. Instead, machine states are made visible through external sensor technology.
Scenario 2: OEE Should Be Introduced, but the Data Foundation Is Missing
A company wants to introduce OEE as a KPI. However, reliable data on availability, performance, downtime, idle time and microstops is missing. Many losses are known, but not measured cleanly.
Here, Novo AI is a very good fit. OEE is only as good as the data foundation. When machine states become automatically visible, OEE can be calculated more reliably and used more effectively on the shopfloor.
Scenario 3: Production Platform With ERP-Related Workflows
A company wants to connect machine activity, work orders, ERP data and production performance more closely. The machines can be connected well, or the organization is ready to systematically build connectivity and data flows.
In this case, MachineMetrics can be the better choice. The platform is designed for connected production data, OEE, downtime, work order context and real-time production intelligence.
Scenario 4: ERP Exists, but Shopfloor Reality Is Missing
Many companies have an ERP system but still do not know exactly what is happening at the machines. ERP knows orders, items, planned times and deadlines. But it does not reliably show whether machines are currently producing or losing time.
Here, Novo AI can close the gap between planning and reality. If a platform or ERP integration is planned later, better machine data is already available.
Scenario 5: Many Modern Machines With a Clear Data Strategy
A company has many modern machines, digital interfaces and a clear goal to use production data comprehensively. OEE, downtime, work orders, ERP information and production performance should be integrated systematically.
Here, MachineMetrics can be a very good fit. Novo AI can additionally make sense where individual existing machines are difficult to connect or where a unified state logic across heterogeneous machines is desired.
Many production data projects become difficult because the foundations are missing. These include clean machine states, realistic planned times, clear downtime reasons, maintained master data and a shared understanding of what is really happening on the shopfloor.
Novo AI can help make these foundations visible earlier. When companies first capture machine states, they recognize faster where the biggest losses occur. They see which machines are frequently stopped, where idle time occurs and which microstops repeat. This information is valuable before a larger platform project is planned.
This can make a later MachineMetrics or ERP integration project more focused. The company then knows better which machines are critical, which data is really needed and which processes have priority. Instead of building a production data project on assumptions, it can be based on real machine states.
Novo AI is therefore not automatically a replacement for every platform solution. In many cases, Novo AI can be a step before a larger production data platform. It creates transparency in the machine park and helps prepare the decision for deeper integration.
Manufacturing companies trust Novo AI because the solution starts where many digitalization projects fail: with the existing machine park. Instead of replacing machines or first starting a large platform project, Novo AI makes real machine states visible.
Companies such as Otto Männer, BlekoTec, Angstrom, Schauenburg Hose Technology, Bockmühlkabel, KUKA Romania, Sorst Streckmetall, Leibinger, Erich Uhe, Jacob Group Pipework and Karl Dungs represent different manufacturing realities — from precision engineering and metal and sheet metal processing to cable, hose, pipe and component manufacturing.
For these companies, theory is not what matters. Everyday production does. Machines need to run, downtime must be detected, idle time must not remain invisible and production decisions need a reliable data foundation. That is exactly what Novo AI was built for.
This practical relevance is important for a MachineMetrics comparison page. Production monitoring can look very good on paper. But the decisive question is whether a company can get the required data from its real machines. If the machine park consists of different years of manufacture, manufacturers and controls, this becomes the challenge.
Novo AI helps companies approach this challenge pragmatically. First, it becomes visible what is happening at the machine. Then responsible teams can decide which processes should be improved, which data should be integrated and which systems should be added.
Misunderstanding 1: Machine Monitoring Is the Same in Every Solution
Machine monitoring can be implemented in very different ways. Some solutions start with machine connectivity and data platforms. Novo AI starts with retrofit sensor technology and AI-based state analysis for existing machines.
Misunderstanding 2: OEE Is Automatically Correct Once Software Is Available
OEE is only as good as the underlying data. If machine states, downtime, idle time and microstops are not detected cleanly, the KPI remains inaccurate.
Misunderstanding 3: A Production Data Platform Automatically Solves Every Brownfield Problem
A platform can be very strong when data is available. However, if old machines do not provide clean state data or are difficult to connect, data capture must be solved first.
Misunderstanding 4: Novo AI Replaces Every MachineMetrics Function
Novo AI does not replace every platform, ERP or Intelligent-MES function. If a company wants to comprehensively connect work order, ERP and production data processes digitally, MachineMetrics can remain relevant.
Misunderstanding 5: Old Machines Need to Be Replaced
Many old machines produce reliably. The problem is often not the machine itself, but missing transparency. Novo AI helps make existing machines data-capable without replacing them.
These companies trust Novo AI
Yes, but only for certain use cases. Novo AI is an alternative when the main goal is fast production monitoring for existing machines without PLC access. If a company first wants to make machine states, downtime, idle time, microstops and OEE visible, Novo AI can be the better entry point. However, if a broader production data platform with machine connectivity, ERP integration, work orders and Intelligent-MES-like functions is needed, MachineMetrics may be more suitable.
MachineMetrics is better suited when a company wants to connect machine, ERP and shopfloor data in a data-driven production platform. MachineMetrics is especially suitable when machines can be connected well, ERP work order data is relevant and OEE, downtime, machine utilization and production performance should be managed through a platform.
Novo AI is better suited when the most important challenge is missing machine transparency on existing machines. If existing machines do not provide clean data, PLC access is difficult or the company quickly wants to see where downtime, idle time and microstops occur, Novo AI is often the better first step.
Yes. For many companies, this is sensible. Novo AI can be used as a transparency layer before a larger platform project. This allows the company to first see what is really happening in the machine park. This data later helps plan integrations and platform functions more precisely.
No. Novo AI does not replace every MachineMetrics function. The solution is not a full Intelligent MES or ERP-related production platform. Its strength lies in retrofit production monitoring and the detection of real machine states without PLC access.
No. Novo AI can detect machine states without PLC access. The external AI sensor is mounted on the machine and uses physical signals such as vibration and acoustics. This makes Novo AI especially suitable for existing machine parks.
Novo AI is especially suitable for small and medium-sized manufacturing companies with mixed machine parks. This includes companies with old machines, different manufacturers, missing real-time transparency, unclear downtime, idle time problems or OEE goals.
The best first step is a pilot with a few relevant machines. Ideally, the company selects machines where downtime, idle time or unclear utilization are already known problems. With Novo AI, these machines can be monitored quickly. After that, the company can decide based on data whether more machines, ERP integration, MDE/BDE processes or a larger platform project should follow.
The decision between Novo AI and MachineMetrics depends on the starting point.
MachineMetrics is strong when a company is looking for a modern production data platform for discrete manufacturing. The solution is suitable for companies that want to connect machine data, OEE, downtime, work orders, ERP information and shopfloor activity more closely.
Novo AI is strong when a company first needs to make real machine states visible. The solution is especially suitable for existing machines, old or mixed equipment, missing PLC access, unclear downtime, idle time, microstops and OEE transparency.
For many medium-sized manufacturing companies, Novo AI is therefore the better first step. Not because MachineMetrics is bad, but because the most important foundation is often still missing: reliable data from the machines that are already in operation today.
If a company does not know when machines are truly producing, it should not start with a larger platform project that depends on this data. It should first make machine reality visible.
That is exactly what Novo AI was built for.
Are you considering whether MachineMetrics or another production data platform is the right next step for your production?
Then it is worth starting with one simple question: Do you already know reliably when your existing machines are producing, stopped, running idle or losing time through microstops?
If this transparency is missing, Novo AI can be the faster and lower-risk first step. Start with a few machines, make real machine states visible and then decide based on data whether platform integration, ERP connection or further automation steps make sense.
Request a demo now and see how Novo AI makes your existing machines transparent without PLC access.
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