We build steering wheels.
A pure solver is a Ferrari with no steering wheel – all horsepower, impossible to control.
Human operators are a perfectly steered Bobby Car – easy handling, but painfully slow.
Arqh adds the steering wheel to the Ferrari, giving operators precise and instant command over high-horsepower optimization.
An Obsession Born From Frustration.
After months sitting side-by-side with fuel dispatchers and airline crew planners, we were stunned. Mission-critical decisions affecting millions in revenue hinged on colour-coded spreadsheets, frantic phone calls, and fragile tribal knowledge.
That experience lit the fuse for Arqh. We're building a system that thinks at solver speed but speaks in human terms—so the experts who keep the world moving finally get the tools they deserve.
The Team
CEO & Co-founder
Computer Science from ETH Zurich. Former president of tech consultancy ETH juniors and member of the high-performance computing team.
An entrepreneur since 15, from running a ginger-shot business to deep-tech consulting.
CTO & Co-founder
MSc in Data Science from ETH Zurich. Machine intelligence researcher at ETH & EPFL, former engineer at Deloitte.
Theoretical AI PhD drop-off after 6 months to pursue real-world impact in business.
Product Manager
ETH Zurich MSc in Machine Intelligence & award-winning researcher at Yale.
Experience in tech strategy at Deutsche Bank and risk management at PwC.
Senior Software Engineer
MSc in Computer Science from NTUU with extensive software development experience across manufacturing and sales industries.
Expert in building robust applications for GenAI and complex data analytics solutions.
From the Lab to the Loading Dock.
Our methodologies are academically-grounded and validated by real-world application. We believe in transparency and advancing the state of the art through collaboration with leading research institutions.
ETH AI Center - Data Science Lab
Learning to Optimize for Petrol Station Replenishment
This work, implemented by ETH students Hanno Hiss and Hannes Büchi and supervised by Arqh, proposes a hybrid reinforcement learning framework to solve complex, real-world Vehicle Routing Problems.
M.Sc. Thesis - EPFL
Adaptive Heuristics for Petrol Station Replenishment
Supervised by Prof. Dr. D. Kuhn and Arqh co-founders, this thesis by Alessandro Dalbesio forms a core part of our engine's foundation, exploring adaptive methods for extended planning horizons.
Ready to Optimize?
See how Arqh can transform your operations. Get in touch with our team to start a trial today.