Our professional career has been a unique (and risky) experiment chasing the Frontier of Knowledge.
We have challenged every single process that has settled in the industry. And we have injected our own style, academically rigorous, to transformation. Both, industry and academia, have prized our approaches.
Our quest seeks to address the optimal legacy required by our clients going forward - from tech and talent distribution to service dependencies. It is their key stepstone in a digital ecosystem and we want to be their one-stop shop.
Before entrepreneuring, as clients of digital transformation, we did eager to find a provider we could leave all responsibility to design and develop a creative but rigorous, comprehensive but bespoke, seamless integrated, and open/DIY solution. We found no one with enough credibility to trust such an strategic asset hence, we decided to devote ourselves to the quest.
We are now becoming an authority in the industry of Algorithmization. Especially, in evolving the Trading Floor to a Trading Cloud. Clients value our capacity to provide holistic packages for them to choose. Nonetheless, old-school use-cases-driven transformation is far from optimal.
Rent their avatars. We believe human professionals can yield significant value in a machine-driven world. It is in the merge of human brains with robot brains where robustness of profitability lies. Hence our pioneer role on this niche of science: ©Augmented Machines. Our long-run obsession.
A.I. researchers typically use real domains to test their techniques. Three prominent peers at UCL used video games to prove their point: "machines are better than humans". It was the seed of DeepMind, now Google's A.I. arm. To prove ours - "machines reinforced by humans are better than machines"- we have selected probably the most ambitious business domain: Algorithmic Trading. And our financial infrastructure has since 2009 achieved outstanding results (more on this at About).
Algorithmization requires new talent with in-depth knowledge in the overlap across several disciplines: it is a hyper-dimensional problem.
Companies will struggle to fulfill such crucial positions within the next decade - the more so the higher the barriers to entry those disciplines (e.g. Financial Computing)
SciTheWorld provides a technology architecture that breaks down the hyper-dimensional challenge into the original isolated disciplines. This way companies can move forward leveraging their current teams - often, completed with a new breed of experts in the discipline of Machine Learning.
This is, we provide the kit for a DIY evolution.
Through our links to UCL's Dept. of Computer Science (ranked #1 in the UK) we keep evolving our Augmented Intelligence alongside some of the best researchers on A.I. in the world.
Furthermore, we also have an in-depth relationship with UK's CDT in Financial Computing & Analytics (UCL, Imperial and LSE) where we mentor top talent on the merge between A.I., tech and risk management.
The Algorithmization of Businesses is a digital disruption that crucially pivots upon a handful of experts. Those who realistically account for a) the business mindset of an economist, b) the accuracy and creativity of a scientist, c) the insights and expertise of a practitioner, and d) the independence and techy acumen of a developer. And the judgement blossoms at the intersection of the four. Not only at their union.
"By merging tier one merits in finance, science and technology, we are quickly becoming an internationally recognized authority in this very special sweet spot"
"Our most aggressive competitor lies in the client itself: its status quo, its change resistance.
We are hands-on experts unlocking the cultural change top-down and bottom-up; hence we carefully select the clients with whom we take the journey on this inmense challenge - moving from a Digital Agenda onto an Algorithmic Agenda.To keep our focus neat and the pace at which we evolve, high, we mostly say no"
"... the more we integrate you with our platform,
the more you can evolve at our own pace"
"We saw in our continuosly-evolving platform an opportunity for our clients to test the future. This way, they can better manage their (always risky) innovation decisions based on data and advanced features"
"We have a systematic approach to innovation. A culture that we have successfully developed along our years as intrapreneurs both in finance and academia.
More subtly, we target to minimize science when achieving a sought impact. Minimal shall not be confused with with low. If minimal requires us to author a whole new approach to A.I., such is ©Augmented Machines , so be it"