MTEK and ETQ’s Recent Partnerships with Microsoft and Acerta Analytics Highlight the Value of Collaboration in the MES and QMS Markets

Artificial Intelligence (AI) and Generative Artificial Intelligence (Gen AI) have arrived, and executive teams are keen to see it deployed across their organizations—in many cases, no matter the cost. ABI Research forecasts that spending on Gen AI will reach US$10.5 billion by 2033, up from US$0.33 billion in 2023, at a Compound Annual Growth Rate (CAGR) of 41% (see ABI Research’s Generative AI Use Cases in Manufacturing presentation (PT-2763)). Technology vendors, particularly those in the enterprise software markets, have been working around the clock to develop and integrate AI/Gen AI functionality into their solutions. Many have identified that an effective way to augment their offerings with these capabilities is through leveraging partnerships with pure-play, best-of-breed, AI/Gen AI solution providers, resulting in a flurry of partnership activity over the past year.

Vendors in the industrial market have consistently partnered with NVIDIA to support their push into the AI and Gen AI space; however, with such a prolific number of NVIDIA partnerships, it is difficult to see this as a notable differentiator for many vendors’ solutions. To stamp their own mark on new functionality, technology vendors must look further afield when building partnership ecosystems to develop unique capabilities.

MTEK recently announced its strategic collaboration with Microsoft in October, using its Manufacturing Execution System (MES) platform MBrain’s comprehensive data collection across the factory floor to power Microsoft Azure AI and Microsoft Fabric tools for a range of functionality, most notably industrial copilots. In the same month, ETQ launched its AI-based Predictive Quality Analytics Solution, which integrates predictive quality analytics software developer Acerta Analytics’ LinePulse solution with ETQ Reliance.

The goal of AI/Gen AI partnerships is to drive the development of strong new functionality to support enterprise software vendors’ solutions. Partners will either bring new functionality that can be directly integrated into the platform or leverage the rich data environments provided by these solutions to construct powerful AI/Gen AI models.

MTEK & Microsoft

AI and Gen AI models and tools are data hungry, and it can be challenging for manufacturers to collect and manage data from across siloed operations and software. MES solutions are an effective option to support this process, acting as the backbone of manufacturers’ production lines. MTEK builds the foundational data layer to power the advanced AI/Gen AI tools offered by Microsoft, with MBrain providing Microsoft Azure AI contextualized data from the shop floor. Furthermore, MTEK has integrated data handling capabilities from Microsoft Fabric to streamline the solution’s data processing.

One of the primary AI/Gen AI applications this process powers is industrial copilots, which can be effectively trained by feeding the existing database built by a client using MBrain into Microsoft Fabric, which can then immediately start providing insights into key manufacturing questions already tailored to the customer’s operations. Mattias Andersson, MTEK’s Chief Executive Officer (CEO), highlights “the very first time Microsoft Fabric ingested an MBrain data-model, it immediately started providing insight into the types of questions all manufacturing engineers really want to answer, but without the effort” (October 2, 2024).

Customers can deploy Microsoft Fabric within their own cloud-tenant alongside MBrain, providing a significant increase in the security of their proprietary data and becoming an extension of the user’s own operations, something of critical importance for many manufacturers when looking to adopt AI/Gen AI tools. MTEK and Microsoft’s partnership not only drives the development of new AI-powered MES functionality, but also drives collaborative Go-to-Market (GTM) activities, with close integration between the two companies’ technology stacks ensuring that as soon as customers are ready to deploy AI and Gen AI tools on their shop floor, the solutions are ready to go, with very little integration work.

ETQ & Acerta Analytics

Ensuring product quality has been an increasing point of concern for many manufacturers. The process of capturing and documenting data, ensuring complete traceability, and tracking product errors can be incredibly time consuming, even with comprehensive Quality Management System (QMS) software solutions, providing a ripe environment for augmentation with AI tools.

ETQ partnered with Acerta Analytics, a developer of predictive quality analytics software, using its LinePulse to launch the ETQ Reliance Predictive Quality Analytics solution. The solution supports early detection of quality issues on the production line and then recommends proactive actions to mitigate these threats, forming a closed-loop quality system.

Acerta Analytics’ AI-driven Predictive Quality Analytics application is fed with data from the shop floor through Acerta’s LinePulse to ascertain the likelihood of a given quality issue. This data are then integrated with ETQ Reliance QMS to enable operators to rapidly conduct Root Cause Analysis (RCA) and identify solutions. Once the issue has been resolved, ETQ Reliance returns feedback to LinePulse, continuously improving the model and predicative quality of the solution in reaction to each customer’s real-time quality data.

The time for talking about AI/Gen AI capabilities is very much ending. Demonstrable functionality that is live and accessible to customers is all that should matter to customers now. For enterprise software vendors looking to drive leadership in this space, symbiotic collaboration between themselves and AI providers is essential to leverage the expertise of both groups and design solutions that truly move the needle for customers.

Both groups hold the key information required by the other to successfully develop AI tools. Manufacturing enterprise software providers hold access to incredibly rich datasets that are essential to the effective training of AI/Gen AI models, alongside a keen understanding of customer needs. Meanwhile, dedicated AI solution providers have a deep understanding of the technical requirements to build strong AI/Gen AI tools and solutions and knowledge of industry-wide best practices. Furthermore, the lack of skilled AI workers in the market is a significant challenge for many technology vendors looking to develop their own in-house functionality. To attract this talent, companies will find themselves competing with the Google, Meta, and Apple.

Technology vendors looking for success when developing new AI/Gen AI tools should be looking for every opportunity to partner with dedicated AI solution providers. These partnerships can primarily take two forms. First, enterprise software providers can quickly look to integrate associated AI/Gen AI software tools with their given solution, rapidly expanding functionality that can be quickly purchased and downloaded by customers. The second is a deeper partnership, where the participants collaboratively build out solutions that meet the specific needs of existing or potential customer bases. This partnership takes far more time to bear fruit and requires a greater degree of alignment between the two companies; however, in most cases, this results in a far more differentiated and valuable offering.