DCbrain: smart modelling of physical networks

May 3, 2017

Whether they carry electricity, gas, steam, compressed air or water, physical networks invariably have two things in common: it is difficult to produce a visual representation of how they are used, and their inherent complexity makes them tricky to optimise.

Benjamin de Buttet, Sales Manager, DC Brain

Benjamin de Buttet, Sales Manager, DC Brain

Thank goodness we now have DCbrain!

Benjamin de Buttet, partner and sales manager of this French software start-up, tells us more about it.

Can you tell us briefly what your software brings to the industry?

Most physical networks – in industry, energy, complex buildings or even logistics – are quite well instrumented so produce large quantities of data. But it is still difficult for network operators to make operational decisions based on that data. This is where our software comes in: it can model a network and, most importantly, the way it operates, based on the data logs and a hefty amount of machine learning (editor’s note: artificial intelligence). It then uses this model to optimise network usage, working through a particularly user-friendly and efficient visual interface. What’s more, we have just won the Data Intelligence Award 2017 in the Data Visualisation / Data Discovery category.

In practice, what purpose does it serve? And who uses it?

The main users are operational network managers, who know their system by heart and have already optimised it to some extent with the conventional tools (and often a good measure of experience-driven intuition). With our real-time simulation tool, they can grasp the systemic aspect of their network (since the parameters are all interdependent) and predict breakdowns and production limitations, etc. Ultimately, they optimise their output even more effectively and save time in the process. Other stakeholders are interested too, beginning with investment managers, who can use it to simulate the operational and financial impact of different scenarios.

Is it expensive? And slow to pay off?

The return on investment is very fast – around a quarter – firstly because our software is very efficient, secondly because our prices are reasonable (editor’s note: calculated on the number of sites and features).

How are you marketing your software?

We still need to go out and win converts with POCs and demonstrators. So, for the moment, we are focusing on direct sales through an in-house sales team. However, because we are ultimately aiming for a global market, we are starting to test the possibility of distributing DCbrain through integrators already established in the industrial community. In the meantime, we are kick-starting our European roll-out with the invaluable help of InnoEnergy, which is giving us access to its circle of business developers.

What else is InnoEnergy doing to help?

InnoEnergy is not just a shareholder, it’s a partner. They’ve managed to strike the right balance between an efficient day-to-day presence (training courses, involvement in strategy and the business model, practical help with industrialisation, and events such as the The Business Booster)… and maintaining our autonomy. Their array of skills and expertise is not only very wide-ranging, it’s also very targeted and innovative. For example, we’re planning to use their offer of assistance with recruiting young doctors, who are very much in demand in our business sector.

What do you have lined up for 2017?

Conclude our current funding round – between €1 million and €1.5 million. Roll out version 2 of the software, which will be even more user-friendly. And of course continue our business development!


DCbrain in brief:

Founded: 2014

Staff: 8

References: GRFD, Enedis, Total, ID Logistics, RATP, Cdiscount, ENGIE, SNCF, Equinix

2016 sales: €200K-€300K