NEW TECH FOODS

It’s easy to get caught up in the news and activities of the industry’s global giants, but what about the smaller firms pushing boundaries with bold ideas? In this instalment of start-up spotlight – which celebrates lesser-known companies and their innovations – we speak to the founders of Polysense.

Can you tell us about the origins of Polysense? What inspired you to bring AI and hardware together to tackle challenges in the food industry?

Polysense didn’t start in the food industry. Our initial mission was broader: exploring how AI could support sustainability across different sectors. We worked with companies like GSK, DEME and Agristo, which gave us valuable exposure to a range of industries. But we soon realized that the scope was too wide to create focused, meaningful impact.

The real shift happened when we began working closely with Agristo. They are a frontrunner in food innovation, and through that collaboration, we saw just how much untapped potential still exists in the sector. We were surprised to learn that around 20% of food input in Europe ends up as waste. If even a company like Agristo had room to significantly improve quality control and reduce waste, it raised important questions about the rest of the industry.

We started digging into the root causes. Most food waste in production isn’t due to a single issue but a combination of factors: process variability, inconsistent raw materials, human error and lack of real-time feedback in production environments. If producers don’t have accurate, in-the-moment insights, they tend to overcompensate, discard borderline product or run inefficiently. All of which leads to waste.

That insight helped us narrow our focus. We saw a clear opportunity to apply AI in a way that was both technically valuable and mission-driven. From that point on, we dedicated ourselves to the food sector and built our expertise around it.

At the same time, our passion for reducing food waste really accelerated. In terms of sustainability, few areas offer such a strong combination of ecological and economic benefits. Reducing waste doesn’t mean adding complexity for producers. It means giving them the tools to better control variability and outcomes with confidence.

That is how Polysense was born: through hands-on experience, a sharp strategic focus and a growing belief that this is where AI can genuinely transform an entire industry.

You recently closed a €2 million investment round backed by several high-profile tech entrepreneurs. How will this funding accelerate your growth, and what are your next key milestones?

Closing the €2 million funding round was a major milestone for us, not just financially but also in terms of the people we now have around the table. The capital allows us to move faster in three key areas.

First, it gives us the resources to push the limits of what our product can do. We’re already solving complex quality control challenges in live production environments, but this funding allows us to go further. We can take on even more advanced use cases and continue to innovate at the core of our platform.

Second, we’re accelerating our international growth. We’re already active in four countries and seeing increasing demand from manufacturers across the world who are looking for smarter, AI-powered ways to reduce waste. With this funding, we can grow our team, stay closer to our clients and make Polysense available in more factories globally.

Third, we’re gaining more than just funding. The investors who joined us bring deep operational experience and a powerful network. Several are seasoned tech entrepreneurs who understand what it takes to scale a product in an industrial setting. Their input has already been valuable across areas like hiring, pricing and strategic partnerships. Having that level of support at this stage makes a real difference.

This round gives us the momentum to keep building, keep learning and scale with confidence. The next milestones are already in motion: new product capabilities, deeper client integrations and continued international expansion.

Food waste and operational inefficiencies are persistent industry issues. How exactly does Polysense technology help manufacturers reduce waste and improve efficiency?

These issues are indeed persistent, but to truly solve them, you need to address the root cause. In food production, the main challenge is natural variability. You are working with organic, living materials that constantly change. No two batches are ever exactly the same. That variability leads to inconsistent quality and unnecessary waste.

At Polysense, we help manufacturers make their processes more resilient to that variability. It starts by replacing manual, subjective quality checks with objective, automated in-line quality control. Instead of relying on periodic human inspections, we generate a continuous stream of real-time, high-resolution data. This provides a far more accurate and consistent view of what is happening in the production line at every moment.

We then use that data to fine-tune process parameters in real time. This enables manufacturers to stabilise quality, reduce waste and improve yield. By moving from reactive decisions based on human judgment to proactive, data-driven control, producers gain the ability to consistently deliver high-quality products, even when raw materials vary.

You already work with major players in the F&B industry. What has the feedback been like from partners using your solution – and what kind of ROI are they seeing?

One of the most important aspects of our impact is that it goes beyond ecology. Food producers are certainly under growing pressure to reduce their environmental footprint, and our technology supports that goal. But what is often overlooked is that sustainability is still too frequently viewed as a cost rather than a value driver.

At Polysense, we show that ecological impact and economic value can go hand in hand. By reducing waste, improving product quality, and increasing process efficiency, we help manufacturers boost their margins while becoming more resilient to ongoing changes in supply, raw materials, and demand.

In some use cases, the return on investment is achieved within just a few months. That is often the moment when it truly clicks for our clients. They realise that sustainability is not only good for the planet, but also a powerful business advantage.

How adaptable is your technology across different food production environments? Are there specific categories or production processes where it delivers the most impact?

A major bottleneck with traditional in-line quality control systems is their heavy reliance on large volumes of training data. This makes them difficult to scale across different food production environments, where each line and product can vary significantly.

At Polysense, we have solved this by developing technology that can automatically generate synthetic data in a virtual environment. This synthetic data is then used to train our quality control models, eliminating the need for manual data collection and labelling.

As a result, our solution becomes far more scalable and can be applied across a wide range of food production processes. Whether it is fries, vegetables or baked goods, our approach allows manufacturers to adopt AI-driven quality control without the traditional barriers that slow down implementation.

As manufacturers look to improve traceability and real-time decision making, where does AI-powered hardware like yours fit into the digital transformation of the factory floor?

In modern food factories, information flows through several layers. ERP systems handle procurement and planning, MES platforms coordinate batches and workflows, and PLCs, SCADA systems and sensors manage and monitor the production process on the ground. Polysense adds a new layer to this ecosystem: AI-powered vision that inspects products in real time.

Our smart cameras connect directly to PLCs and SCADA systems, generating a continuous stream of objective quality data. This data can feed upstream to improve decision-making, even in factories that do not have an MES. Operators and control systems gain immediate visibility into anomalies, allowing them to act before issues escalate.

When an MES is present, our data integrates seamlessly. It strengthens defect detection, enables real-time feedback loops, and enriches both MES and ERP records. In cases where no MES is in place, Polysense operates independently. We can adjust setpoints directly via PLCs or provide actionable insights through our own dashboard. This makes production control more intelligent, no matter the existing setup.

The result is a shift from reactive to proactive manufacturing. Polysense gives the factory floor a new layer of perception. You catch defects before they lead to waste, you trace every inspected item, and you stabilise operations across the board. All of this happens without needing to replace or disrupt the current infrastructure.

By filling critical blind spots in the control stack, we help manufacturers increase yield, reduce rework, maintain compliance, and improve margins. This is operational intelligence designed for the real world – live, practical and built for industrial environments.

Sustainability is a growing concern in manufacturing. How can your tech support companies in meeting ESG targets or complying with environmental regulations?

When talking about ESG targets, it’s important to understand how they’re actually measured and reported. With the upcoming CSRD regulations in Europe, companies will soon be required to report on their environmental impact – specifically in terms of CO₂ emissions per ton of product produced.

Targets will be set to lower that footprint as much as possible. What we do at Polysense directly supports that. By reducing waste, manufacturers generate more usable output from the same resources.

That means the total CO₂ emissions can be spread over a larger volume of product, resulting in a significant reduction in their sustainability impact – and making it easier to meet those regulatory goals.

What have been some of the biggest technical or commercial challenges you've faced as a start-up – and how have you overcome them?

When talking about ESG targets, it is important to understand how they are actually measured and reported. With the upcoming CSRD regulations in Europe, companies will be required to report on their environmental impact, particularly in terms of CO₂ emissions per ton of product produced. Targets will be set to reduce that footprint as much as possible.

Polysense directly supports that effort. By reducing waste, manufacturers produce more usable output from the same amount of raw materials, energy, and water. This means the total CO₂ emissions are spread over a greater volume of product, lowering the environmental footprint per ton.

Just as important, we help prevent unnecessary production runs. When quality issues go undetected, entire batches often need to be reworked or scrapped. With Polysense in place, manufacturers can catch problems early, avoid reprocessing, and prevent low-quality batches from being produced in the first place. That leads to better resource use, lower emissions and more stable operations.

In short, we help manufacturers not only reduce waste, but also avoid producing waste altogether. This makes it significantly easier for them to meet ESG targets and comply with emerging regulations – while improving efficiency and margins at the same time.

What advice would you offer to other food-tech start-ups aiming to work with established manufacturers or break into the B2B space?

Breaking into the food industry as a start-up is not easy. You are often dealing with large manufacturers who are risk-averse and rely on processes that have been running the same way for years.

My biggest advice? Do not lead with 'AI' or 'innovation'. Lead with a real problem they feel every day on the production floor.

Start by understanding how their process actually works – not just on paper, but in practice, side by side with the operators. Focus on something specific you can improve, and make sure your technology fits into the way they already work. That is how you build trust.

Once they see that you are not just another flashy tool, but something that actually improves yield, quality, or reduces downtime, then you have a real foothold. From there, everything becomes easier.

Looking ahead, how do you see the role of AI and smart hardware evolving in the food industry over the next five to ten years? And how does Polysense plan to lead that change?

Over the next five to ten years, I believe AI and smart hardware will become as embedded in the food industry as ERP systems are today. The real shift will be in how production decisions are made. Currently, many decisions still rely on gut feeling or manual checks. In the future, factories will be far more autonomous, with quality monitored continuously and processes adjusting themselves in real time based on what is happening on the production line.

This is exactly where Polysense wants to be. We are building a future where every product is measured, every process is optimised on the fly and operators are supported by intelligent systems that help them make better, faster decisions. Our goal is to become the quality layer of the factory, a real-time connection between what is happening physically and what needs to change digitally.

If we succeed, AI will no longer be just a nice-to-have innovation. It will become an essential part of how food is made, making production more efficient, more consistent, and far less wasteful. This is the future we are working toward, and we want to lead that transformation.