Instrumental Closes $50 Million Series C to Accelerate Manufacturing Optimization Innovation

Manufacturing optimization software provider Instrumental closed US$50 million in Series C financing in February 2022 to expand research and development for new products and make critical hires in engineering and go-to-market teams. The company builds core manufacturing data infrastructure for leading electronics brands such as Cisco, Honeywell, Foxconn, and Flex for both New Product Introduction (NPI) and manufacturing production applications. These brands use Instrumental’s cloud-based Artificial Intelligence (AI) software to perform quality control remotely without the need to be on site. The growing appetite and demand for this new category of solutions is evidenced in the 3x bookings growth and 150% net revenue retention it saw in 2021.

The Manufacturing Optimization Ecosystem exists between slow-moving and expensive one-time human audits and rapid real-time business intelligence tools. It encompasses many industries and verticals to address the different problems that need to be solved as well as the different kinds of data used to solve those problems.

For example, process-driven manufacturing has a lot of machines, so machine data is a key data source for optimization. Discrete manufacturing produces many individual items, so product data is a key data source for optimization. Supply chain works with supplier processes, availability, and order fulfillment, so supply chain data is a key source for optimization. Traditional manufacturing systems and domains such as Computer Aided Design (CAD), Manufacturing Execution System (MES), and test and measurement serve as inputs.

This ecosystem came to bear as result of the need for more agile and proactive optimization techniques in manufacturing. While consultants remain well-suited for industries that don’t change the line frequently, such as automotive and food and beverage manufacturing, they are poorly suited and completely unutilized in most fast-moving industries like electronics manufacturing.

Instrumental helps collect the data that manufacturers create as part of their normal testing process and overlay that data with new sources of information like vision data. The biggest benefit isn’t just the discovery of problems but automatic root cause analysis, which is an activity that traditionally occupies a significant amount of engineering time and resources when done manually.

The challenge is that many manufacturing companies and their brand partners work on a reactive basis, leveraging reports from factories as a baseline capability. Some have real-time access to parametric data, but it is not necessarily actionable. The ability to leverage actionable data would be another, more advanced level that includes live reporting, real-time alerts, and unit-level drill down capabilities for the entire team, but very few companies have started to standardize and scale these kind of analytics (bearing in mind there is a long tail of small to medium size manufacturers, as detailed in MD-MMD-101). Ultimately, the goal is for AI-powered data anomaly detection and correlation discovery across mixed data types for true optimization.

Instrumental (product data) is among a cohort of companies including Seeq (machine data), Plex (supply chain data), and Drishti (human process data) that are focused on leveraging and optimizing data correlations automatically with software. While Instrumental already works with some of the largest brands in the electronics space, its cloud-first approach and Software-as-a-Service (SaaS) orientation make it an attractive partner to test and learn in adjacent industries like medical devices, appliances, or even aerospace. It is also a likely partner target for technology suppliers in other parts of the manufacturing optimization ecosystem, including CAD and MES providers like PTC, Siemens, and Rockwell Automation.