High-precision metal components are crucial to manufacturing, yet programming CNC machining equipment remains a manual process. With a shortage of skilled workers [metal machine setters were among the top five most in-demand occupations in Europe in 2023] manufacturers are under pressure to streamline operations. Rising geopolitical tensions, cost concerns, and the shift towards regional supply chains further compound these challenges.
ETH spin-off Manukai raised $3M [CHF2.645 million] in an oversubscribed pre-seed funding round. The round was led by Swiss VC QBIT Capital and participated in by Bloomhaus Ventures, Innosuisse, and a group of angel investors. The investment will help fast-track the development of Manukai’s patent-pending AI technology, bringing it closer to market readiness.
This marks a significant step towards transforming CNC machining through artificial intelligence. The startup has established relationships with industry leaders like Bosch. They will use the funds to refine their AI-powered product, aiming to enhance efficiency in CNC machining.
A data-driven approach to CNC machining
Manukai was co-founded by Pascal Weber and Daniel Wälchli in December 2023 and is developing AI technology that integrates seamlessly with existing CNC programming tools. They both hold doctoral degrees from ETH Zürich and Harvard University. Their expertise in AI engineering, guided by Torbjørn Netland, has been crucial. Torbjørn Netland is Co-Founder at Ethon AI and Professor at ETH Zürich. This guidance has been instrumental in developing Manukai’s innovative software.
One barrier to AI adoption in CNC machining is the need for strict privacy controls and compatibility with established workflows. Manukai’s software package allows manufacturers to centralise institutional knowledge, accelerate programming, and optimise machining efficiency without disrupting existing systems.
Its patent-pending solution enables manufacturers to leverage historical data on-premises while maintaining stringent privacy requirements.”Our vision is to become the leading AI technology company for manufacturing,” says Pascal Weber. “By unlocking the value of the vast manufacturing data, we enable our clients to boost their production efficiency.”
“What truly sets us apart is our data-driven approach,” says Pascal Weber, CEO and Co-Founder of Manukai. “Our algorithms leverage client data within their secured environments, ensuring total IP protection while enhancing CNC programmers. Rather than attempting to replace human knowledge, we amplify it by easing access to past programming strategies. This approach respects that the worker’s experience is the gold standard—we simply help them access and apply that knowledge more efficiently.”
Pioneering AI automation in CNC programming
Manukai is redefining CNC programming by using AI to automate and optimize high-precision metal machining. By leveraging machine learning, the company aims to reduce programming time and improve machining strategies. Additionally, they address the industry’s widening skills gap. With strong backing from investors and a team of AI specialists, Manukai is looking to reshape the future of CNC manufacturing.
“Manukai exemplifies how AI can unlock immense value from legacy data, revolutionising manufacturing efficiency worldwide,” says Georges Khneysser, Founder and GP of QBIT Capital. “With Switzerland’s unmatched industrial heritage and Zürich’s cutting-edge AI ecosystem, Manukai is poised to lead the global evolution of manufacturing.”
Pascal Stürchler, Co-Founder and CEO of Bloomhaus Ventures, adds: “Manukai is tackling one of the most pressing challenges in manufacturing with a groundbreaking AI solution. By removing key inefficiencies, they are unlocking new levels of productivity and competitiveness for manufacturers worldwide. Their strong founding team, combined with a scalable and industry-agnostic approach, positions them for lasting success. We are excited to support their journey and see them drive real change in the industry.”
Source: https://techfundingnews.com/
