Audience Opinion Piece

Please can you give a summary of your role and main responsibilities?

I’m the Founder and CEO of Squint, a Manufacturing Intelligence Platform. As a founder, my role kind of changes daily depending on what’s needed for the company to execute at the moment. These days, I spend a lot of my time talking to our customers and thinking about new ways our product can create efficiencies on factory floors across America.

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How long have you been in your current role and what do you enjoy the most about it?

I founded Squint in 2021 and have been CEO since. But my role has changed drastically as we’ve scaled from one person to over 50 people. The thing I enjoy the most is seeing the impact Squint has on our customers. I love talking to operators at the facilities that use Squint and hearing the stories of the difference it is making in their operations. I recently talked to an operator who explained that prior to Squint whenever there was a fault at their station they felt nervous that they did something wrong and helpless because the only solution was to wait for maintenance to come diagnose the issue. With Squint, most common issues are now addressed directly by the operator and they feel much more confident and have seen their performance improve because downtime is minimized at their station!

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In today's rapidly evolving manufacturing landscape, what do you think are the most pressing challenges that manufacturers are facing?

Simply put, manufacturers are being asked to do more with less. They’re navigating generational turnover, leaner staffing models, and are being asked to reduce scrap and decrease downtime.  

Turnover is higher than ever and the demand for scaling manufacturing in the US is also spiking. These two trends are at odds – we have more manufacturing demand and we have fewer people that know how to work these floors than ever before. For example, some of our customers are seeing 75% turnover year over year. As of 2019, the average tenure on the shop floor was 20 years, and in 2024 it was down to just 3 years.

As a result of the above, manufacturing in the US is facing a crucible moment: manufacturers not only need to capture the decades of expertise before it vanishes but also need to quickly deploy that intelligence and upskill all operators if American manufacturing is going to scale to support the growing economy.

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When addressing these challenges, what steps do you think manufacturers can take to secure some quick wins.

Change management (or the process in which change is introduced to the workforce) is key in successfully rolling out new technology, and perhaps the hardest part of the digital manufacturing journey. Let’s look at an example of rolling out a new mobile app to a factory that has never had iPads before.

Couple tips:

- Explain clearly what the intention of the new technology is. It may sound obvious to the management team that a new app is intended to support operators by reducing quality issues and increasing safety, but proactively clearing the air with operators goes a really long way. Simply explaining that the new AI product is not intended to reduce headcount will put operators at ease and increase adoption of the new technology to help increase operational efficiency with a motivated workforce.

- Don’t lock down the iPads to be work-only. I know this sounds counter-intuitive. Allow operators to use the devices for some personal use cases alongside the new app workflow. This introduces minimal IT risk if you enforce a firewall but allow for simple personalized workflows and web browsing. Ultimately, it creates positive association with the device and results in better caretaking of the hardware  and better adoption of the new technology.

- Tying new projects to metrics and clearly communicating what good looks like and what the goals are before kicking off is important. Always prioritize metrics that impact the bottom line, for example downtime and scrap over time to proficiency. Downtime and scrap clearly impact the bottom line, whereas time to proficiency is a leading metric for what may ultimately become decreased downtime or scrap.

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Can you share a specific case study where you have helped a manufacturer achieve a significant improvement in productivity, efficiency, or sustainability?

Let me give you an example of a story I heard from one of our tire customers the other day. For some background, one of the most important metrics to tire manufacturers is the amount of waste they produce. Waste is the material that goes into tire-making that doesn’t become a tire. So it is material they paid for but couldn’t sell. The waste that is produced due to operator error is a big focal point of continuous improvement efforts because that can directly improve margins. This customer has been using Squint now for about 6 months and they compared quality rates and waste rates between the lines that have Squint and the lines that don’t. The Quality Manager at this factory came to us and said: this data looks fake but it isn’t, we checked it 3 times… we’ve completely eliminated waste from operator error with Squint. Not a single operator has made a mistake on the line since they got Squint.

That’s the kind of impact we’re seeing amongst our customers, it’s completely changing the way they can work, the way they can hire, and their ability to hit their goals.

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What role does data play in your role and/or solution? How do you help manufacturers leverage data to gain valuable insights and make data-driven decisions?

Over the past couple of decades, manufacturers have invested heavily in building up their ability to gather data from the floor and as a result have created efficiencies through observability. One critical area where data is missing is the human actions taken during a shift. We have sensors that capture inputs and outputs from the machines, but are missing data on what the operators are doing that result in production variance. Squint is able to capture precise data automatically through the camera of a mobile device what actions each operator took during a certain process. This allows manufacturers to see trends like which processes are most confusing and which operators are most skilled (and at what). With this visibility, they can understand key breakpoints in their processes and invest in the right solutions.  

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What emerging technologies are you most excited about in the context of manufacturing, and how are you integrating them into your solutions?

Manufacturing is evolving beyond rigid workflows and static knowledge repositories. The next era is Agentic Manufacturing — where AI-driven agents actively enhance, adapt, and guide production processes in real time. Squint is pioneering this transformation by embedding intelligence directly into manufacturing operations, making expertise accessible at every step.

With AI-generated SOPs, Squint converts videos, PDFs, and legacy documents into dynamic, interactive work instructions, ensuring that knowledge is always up-to-date and instantly usable. Our Copilot connects to complex data sources (like wiring diagrams and multi-dimensional tables) allowing operators to resolve issues on the floor without endless searching. To capture and preserve institutional knowledge, Squint’s AI tribal knowledge agent interviews experienced workers, extracting insights and embedding them into a wiki, existing procedures, and Squint Copilot’s Q&A system. This ensures that hard-earned expertise from the floor lives on forever. Finally, our AI step verification allows management to define quality benchmarks visually using the camera. AI then visually verifies each step in real time, automating validation where possible and guiding operators where human judgment is needed.

Agentic Manufacturing means that knowledge isn’t just stored — it’s active, adaptive, and embedded into the flow of work. Squint makes this future possible, ensuring that factories become more intelligent, resilient, and continuously improving.

What advice would you give to manufacturers who are just beginning their digital transformation journey?

Listen to your employees. If they won’t adopt it, it doesn’t matter if it works.  

Crawl -> walk -> run; engagements can die quickly if you try to boil the ocean.  

Embrace change. Change is uncomfortable, but running away from the right answer because of sunk cost fallacy will only delay the inevitable.

I think most industry leaders are looking to technology to create the facility of the future. Our platform is the hub to do that, it enables this flywheel that starts with using AI to capture expert knowledge, then making that knowledge available in formats and screens that people are used to using (like short form videos or AR on a phone or a tablet), and finally by using the intelligent layer of insights that are based on data from the field to improve operations.

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How does your company contribute to the development of a skilled workforce in the manufacturing sector, ensuring that employees have the necessary skills to thrive in this digital age?

Our mission is to make every operator an expert. That means Squint can be the expert in each operator's pocket that gives them the confidence to perform standard work quickly.  

Squint works on Android and iOS devices (phones and tablets), with the goal being to meet operators where they are — removing the need to train people on new and complex hardware, like headsets, and instead providing a simple, intuitive technology layer that just works.

The biggest cause of operator mistakes and ultimately turnover is a lack of confidence in their work. Squint is the missing layer of confidence on the factory floor; it’s able to surface “just-in-time” insights and guidance to operators when they are troubleshooting an issue they haven’t seen before or don’t remember the exact resolution to one of the error codes on a machine. For example, when an operator is unsure of how to proceed, they can speak with Squint Copilot in natural language and ask questions about what they are supposed to be doing. Squint Copilot will surface resolutions based on the OEM equipment manuals and past operator experiences that it’s seen, providing an immediate resolution that minimizes downtime and maximizes operator safety.

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‍Why do you support the 4^th MX.0 Southeast event and what are you hoping to take away from the conference?

We love supporting the MX.0 events because it’s one of the only shows in the country where technology companies, shop floor experts, and manufacturing executives can come together and discuss in an open forum what is happening in industry and how to tackle these challenges. I’m looking forward to hearing the challenges our customers are facing in 2025 and hope to have some engaging conversations around the future of manufacturing intelligence!

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