Interview - Cuurios

Cuurios is a young Dutch software engineering company founded by Leen de Gaaf and Gaetan Giraud.

They position themselves as innovation accelerators who apply Data Science to address complex business problems. Their work goes beyond crunching the numbers, they invest in understanding industry specific context and challenges to deliver software platforms that allow their customers to transform their proprietary data into actionable insights.

We caught up with Gaëtan and Leen last month over coffee and chatted about both where they are today and where they are headed in the foreseeable future.

Can you give us a little background on your interest and your background in Data Science?

Leen: I studied Mechanical Engineering and during my Master’s where I specialized in the field of Man Machine Interaction. The key motivating factor in my career has always been to support people with software solutions that give them the right information at the right time to make the best decision possible. I have since learned that Data Science techniques can be of great value to translate data to valuable information.

Gaëtan: I have a degree in Computer Science/Telecommunication, as well as considerable experience in the field of IT and software. I am deeply convinced that technology does not live in and of itself; the value of IT can be measured in its use scenarios:  supporting decisions making, monitoring and managing one’s business operations. As my career develops, I have tried to practice what I preach:  analyzing, designing and developing solutions for specific business challenges. Over the last few years, I have developed a keen interest in AI and Data Science, which provides business with a radically different paradigm for leveraging software engineering and information management.

What is the context and the objectives of your current work?

The key here is the importance of context. In our experience, most of the data science projects we come across are more data-centric than focused on use cases: Data by itself doesn’t have much value until its used to explore, to test, and to learn from real-live challenges and opportunities.

Unfortunately, most data science projects today seem to follow the same script: “Here is all our data, could you please perform your magic data science trick?” Too rarely Is the question asked, “What is the problem we are facing, could our data help us solve that puzzle?”

Actions should be the inherent outcome of your data pipeline, in other words use your data to incite real world changes. Our philosophy is to keep Data Science simple by developing use cases that add value right away. If you do not transform your data into actions, great potential remains untouched!

Examples of our own work that illustrate this vision include :

  1. Product quality monitoring, our application detect deviations in product quality in the early stage of complex chemical batch processes. We leverage machine learning algorithms to determine the product quality based on time series of historical process and environmental data.
  2. Our Equipment Performance and Efficiency Advisor, an application that provides automatic notifications based on various performance and efficiency use cases (one of them being the optimal moment to clean an asset)

We believe that only by providing concrete, tangible applications can we deliver tangible value to the business and make data an integral part of our customer's daily operations. As such we design custom software solutions to address our customers' challenges and opportunities. 

What opportunities do you see for Data Science in your field and market? 

Our customers (and prospects) are large industrial corporations that have a large stock of proprietary that they have gathered over the years, usually accessible through either data warehouse or a data lake. 

Despite this potential gold mine, they struggle to find the people, time and tools to exploit the data and transform it into relevant operational insights and actions. Moreover, most customers of our customers haven’t captured, or created, the metadata needed to interpret the massive amount of data at their disposition and apply Data Science to its fullest.

This context is usually to be found in the expertise of operators and domain experts - it is difficult to build a coherent picture without the support of a software solution.

  • We believe in doing things in the right order, beginning with mapping and automizing what we call informal data streams
  • We can then apply Data Science methodologies that add value directly to the organization.
  • On the horizon we see a virtuous circle or reinforced learning where actions are suggested by algorithms, enriched by people and then fed back as input to the algorithms.

A case in point would be one of our current clients, a large Oil & Gas corporation operating in the North Sea. We are enriching the value of their data by creating, managing actionable insights using data from their own operational database, creating an integrated data / actions platform. 

What specific advice can you offer students interested in developing their data science skills today?

Leen: Never forget that the data you are analyzing cannot be extracted from its real world context. Take the time to understand the situation before you deep dive in data techniques…

Gaëtan: Practicing data science requires knowledge of databases and data formats, coding (mostly Python, but a bit of C might be required) and a “cuurios”, inquisitive, analytical mindset. Data Science isn’t as a profession as much as a mindset of how you look at the world around you!

Image Credit : Oracle Corp. 


In this issue :

Ethics of Data Science

The Ethics of Data Science

The increasing digitalization of human activity shapes the very definitions of how we evaluate the world around us


The BAI Spring Session

Coaching on Demand

BAI is proud to announce a new service of coaching on demand for your Data Science team.

The Business Analytics Institute

BAI Fall Session 

The Business Analytics Institute and SDMIMD will be offering a 10-day Fall Session on the ethical implications of data science September 6th to 15th in Mysore, India 

 The Ambassador Program

Technologies and Innovation

Prof. Lee Schlenker facilitated the “Technology and Innovation” module of GEM’s Specialized Masters in Digital Strategy this month in Paris, France

Partner Interview

Partner Interview - Cuurios

Cuurios is a young Dutch software engineering company founded by Leen de Gaaf and Gaetan Giraud


 Nearest Neighbors

Getting to Know your Nearest Neighbors

What is k-NN, how does it work, what are its use scenarios, and how has it facilitated innovations in facial recognition technologies?


This Newsletter has been created specifically for the BAI community to foster conversation around the use of analytics in improving business decision-making. 

Interested in our March Newsletter? It can be found here