Skip to content
MarketScale
‹ Back to IndustriesSoftware & Technology

Autocanteen Optimises the Checkout Process with Artificial Intelligence

Like in many industries today, artificial intelligence (AI) is shaking up everyday, normal life. For the food service industry in particular, it’s already seen in the data collection and supply chain optimisation, and now a new vendor is looking to optimise the checkout process, too. Intel’s Mike Philpott, Partner Sales Development Manager and host…

This story was produced through MarketScale. See how Software & Technology teams put it to work with Executive Thought Leadership.

By Mike Philpott · Artificial IntelligenceAutocanteenAutomationContactless Self-checkout Solution
Share

Key takeaways

01

Like in many industries today, artificial intelligence (AI) is shaking up everyday, normal life.

02

For the food service industry in particular, it’s already seen in the data collection and supply chain optimisation, and now a new vendor is looking to optimise the checkout process, too.

03

Intel’s Mike Philpott, Partner Sales Development Manager and host…

Like in many industries today, artificial intelligence (AI) is shaking up everyday, normal life. For the food service industry in particular, it’s already seen in the data collection and supply chain optimisation, and now a new vendor is looking to optimise the checkout process, too. Intel’s Mike Philpott, Partner Sales Development Manager and host of Optimising the Future podcast, spoke with Sergii Khomenko, co-founder of Autocanteen, about how the organisation’s technology is transforming restaurant, catering, and canteen operations by providing a contactless self-checkout solution through the utilisation of AI.

Khomenko explained where the inspiration for Autocanteen came from, and like every good story, it came from a common, everyday experience. While at a lunch, Khomenko witnessed a cashier performing very monotonous work to process payments. The checkout procedure was time consuming and manual, which meant the queue for getting customers through was lengthy and slow. As one can imagine, nobody likes waiting in a line, especially when they are hungry and ready to eat, so losing customers due to time or dissatisfaction is an issue. Because of this experience and observation, Khomenko and his colleagues began wondering if automation was an option for the canteen checkout process.

Using computer vision and machine learning, Autocanteen created an innovative checkout process that is capable of processing an order and checking out a guest in a mere 10 seconds — significantly shortening the queue, increasing checkout throughput, decreasing food waste, and ultimately leading to a higher revenue stream. However, the road to making these big outcomes in the food service industry did not quite go according to plan… at first.

“By the time we had our product production-ready, the world faced the COVID pandemic, and at that time, hospitality was heavily affected with many sites closed and employees had to requalify,” Khomenko explains. “Fast forward a year or two, businesses reopened, so restaurants reopened, cafeterias, canteens, and it was challenging for these businesses to hire staff again.” This is where Autocanteen was able to showcase the many benefits of its ground-breaking technology and solve a big gap in the food service industry by extending capabilities through self-service, reducing manhours needed to run an establishment, eliminating queues, and reducing waste.

To discover more about Autocanteen’s AI solution, connect with Sergii Khomenko on LinkedIn or visit Autocanteen’s website.

About the author

MP
Mike Philpott

Software & Technology: are you visible to AI?

Before they reach out, Software & Technology buyers ask AI engines which vendors to trust. See how AI describes your company today, and where competitors show up instead.

Free workspace

You just read one Software & Technology expert. Imagine publishing your whole team.

This article was produced through MarketScale. Create a free workspace and turn your own team's Software & Technology expertise into the articles, video, and social content B2B marketing buyers in your industry are searching for. No credit card, no demo required.

NPS +73 · 1,000+ creators · 38+ countries

What you get, free

Your own MarketScale Studio workspace
One video edit a month, on us
AI writing, editing, and publishing tools
In-platform coaching to learn the system

More Software & Technology Insights

Enterprise AI hits an inflection point: governance, agentic systems, and the ROI reckoning

Enterprise AI hits an inflection point: governance, agentic systems, and the ROI reckoning

Enterprise AI is transitioning from experimentation to a focus on accountability. Key areas now influencing success include agentic systems, budget scrutiny by CFOs, and robust data governance initiatives. These factors play a critical role in determining the efficacy and ROI of AI implementations in businesses.

  • 01Agentic systems are becoming crucial in enterprise AI for ensuring efficient, autonomous decision-making.
  • 02CFOs are scrutinizing AI investments more closely to ensure their alignment with budget constraints and ROI goals.
  • 03Robust data governance is essential in capturing the full potential of enterprise AI.

Jul 21, 2026

AI governance gaps are blocking enterprise scale-up across the Middle East

AI governance gaps are blocking enterprise scale-up across the Middle East

AI governance challenges are preventing many businesses in the Middle East from scaling up their AI deployment. While technology advancements are not a barrier, the lag in internal governance frameworks is slowing down AI adoption. Addressing these governance gaps can accelerate the integration of AI within enterprises.

  • 01AI adoption in the Middle East is hindered by outdated internal governance frameworks.
  • 02Technology is not the limiting factor for AI deployment; governance is.
  • 03Improving governance frameworks can accelerate AI scale-up in enterprises.

Jul 21, 2026

Palo Alto Networks CEO puts a number on the AI cost problem: 90% token price drop needed

Palo Alto Networks CEO puts a number on the AI cost problem: 90% token price drop needed

Nikesh Arora, CEO of Palo Alto Networks, stated that for enterprise AI to scale, token costs must decrease by 90% within two years. He highlighted that high costs have already impacted companies like Uber, which spent its full-year AI budget by April.

  • 01Token costs for AI need to decline by 90% in two years for scalability.
  • 02Uber exhausted its annual AI budget by April due to high costs.

Jul 20, 2026

Explore More Software & Technology Insights

Read more expert perspectives from across Software & Technology.

Browse Software & Technology Hub

About the Expert

MP
Mike Philpott

For B2B teams

Your experts could be publishing here

Stories like this one run on content MarketScale captures from real practitioners. See how your team's expertise becomes coverage in Software & Technology and beyond.

Book a 15-minute demo

Or call us. No forms required. We pick up. 214-945-2512