Colin Francis (Co-owner)
is a leader in multi-modal logistics. During the Cairo Technologies period he built the award winning optimisation system called PARIS. He has now shifted his focus to VINNI – smart, personalised Matching and Recommendation systems.
My Background – 10 years (Owner) Cairo Technologies, Cambridge and Rotterdam (1993 – 2003)
My company built the award winning logistics software called PARIS http://www.parisoptimalplanning.com This is today owned and operated by Hutchison Whampoa, the world’s largest ports operator.
At Cairo I employed a team of 30 computer scientists, mathematicians and PhD’s who specialised in things like robotics, neural networks and developed high end systems. Many on the team studied at Oxford and Cambridge in the UK. Our environment was casual but intense, often working day and night to debate the merits of proposed solutions to difficult and worthwhile problems. My philosophy is ‘no problem can withstand the onslaught of sustained thinking‘.
I have spent my working life in freight transportation – building intelligent technology to optimise trucks on the roads, reduce empty mileage, air pollution and road congestion. The companies that used this technology included Shipping Lines: Hamburg Sud, Sea-land, MSC and Railroads: CSX and DB.
I am now applying these skills and knowledge to help other industries though VINNI.
Dr. Jonathan Clarke (Co-Owner) Computer Scientist, Engine Designer and System Architect.
I have a PhD in Semantic Reasoning. I took the navigational and diagnostic principles of an autonomous underwater robot and applied them to the complexities of Machine Translation of Ancient Egyptian.
I also built Artificial Neural Networks to measure how chaotic corporate production systems have become. I then used them to apply reactive controls to provide the user with a smoother, faster and load-balanced real-time experience.
I have been working in the field of logistics optimisation for many years, as well as delivering commercial strength Artificial Intelligence solutions to clients as part of an independent consultation role. This has been an extremely successful niche, where typical, anecdotal A.I. implementations are not necessarily backed by commercial rigour. On a commercial note, the challenges have been to select an appropriate medium between cutting edge platforms and proven frameworks to underpin made-to-measure implementations that have been fit-for-purpose. This has meant the selection from a variety of implementation paradigms, including cloud-based Ruby on Rails systems, deployed to Heroku, through to dedicated server based implementation, providing endpoints for MongoDB repositories and software engines for autonomic data mining. Such implementations are undertaken with a keen eye on financial and time constraints, as well as the technical implications of these recommendations.