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What

Knowledge is power. Power to grow, power to thrive. Knowledge is information acquired through experience - knowledge is data.

Your power, your growth, your future lies within the data of the past. Ask the right questions, connect the right dots, and start your data-driven journey to the future with us.

Because Cuurios:

  • learns from what happened yesterday,
  • knows what's happening today,
  • predicts what's going to happen tomorrow.

Automate, formalize, improve your data analysis and take your data to the next level: use the open-source Cuurios software to turn it into concrete actions.

Your history, your data and your domain expertise will be more valuable each day.

We are curious and personal: Cuurios gets the job done.

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have a question?

+31(0)85 0608400
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what

Why Cuurios

A vast number of Excel sheets, years’ worth of data that only takes up storage on the server, hours of manual data analysis every week or month, numerous separated applications and multiple complex databases containing the same data relations but not in connection with each other?

Struggling to optimize your company’s data, keeping the information up to date and available for everyone at the same time is a real challenge.

Taking your data analysis to the next level not only saves you time, but can help identifying patterns, tracking events in real-time. With our automated solutions:

  • your decision making will become faster,
  • you will know exactly what areas need your attention,
  • you can use your energy on moving forward instead of analysing what happened manually,
  • you can access and share information on just one platform, real-time and through the whole organization.
Do you
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+31(0)85 0608400
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why

The people

Leen de Graaf

Leen de Graaf

Founder and Operational Director

I get energy from bridging the gap between the customer’s daily reality, new technology and software development. I’m enthusiastic, curious and people oriented. I strive towards making the most out of every opportunity by employing a driven approach: always go one step further!

Gaëtan Giraud

Gaëtan Giraud

Founder and Technical Director

Result-driven, inquisitive and professional − these words characterize me. My heart beats faster when making discoveries and achieving new heights with technology.

Tamara Nagy

Tamara Nagy

Full-Stack Software Developer

I enjoy working with the newest programming techniques so that everything is synchronized with what the company needs to capitalize on the market. At Cuurios I can continue learning and have the opportunity to grow which is important to me.

Reena Choudhary

Reena Choudhary

Full-Stack Software Developer

At Cuurios, I’m constantly challenged. Working for a software start-up is a fantastic experience because you’re continually developing yourself. Besides this, I enjoy working in an informal environment with a team of professionals.

Michael Bolaji

Michael Bolaji

Frontend Software Developer

Working at Cuurios is the best decision for my career. I've learnt a whole lot (it's an ongoing process). I stay up late at times, review more codes, ask many questions and in all, write better code. I've learnt that data is simply a waste, until actions can be taken on them.

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people

Blog posts

Sneak peek: this is how we build software at Cuurios

A couple of introverts sitting in front of multiple dark screens with green or white texts running on each, typing with untraceably fast fingers, only the keyboard clacking breaks the silence...

Although during the last decade the perception of programmers may have changed: instead of mom’s basement, they are now imagined in a fancy, futuristic, well-equipped environment, the basic personality traits of geeks are still perceived the same.

Just typing, and typing all day...

... well honestly, no. As software developers we spend most of our times with designs, research and problem solving. We could actually sit down and start writing your application the second we got the assignment, but that’s not the effective way. You want good, steady result, fast, and there is only one way to that: design, plan, research, and finally code.

Yes, we can type fast. Yes, we can sit in silence and focus for 8 hours without so much as taking a lunch break – or at least some of us can. Yes, we are coding in the evening, in the weekend, in our freetime, even in our dreams sometimes – because we LOVE solving problems. Give us the most complex ideas, the impossible tasks, and we will trigger happy, and start working on them straight away.

Yes, we ARE geeks, but that doesn’t make us mysterious, unapproachable, introvert or unsocial. We can easily come across arrogant, but most of the time it would just take forever to make you understand the details – we don’t have God complex, we just know, that it’s better to get it done, than explaining how will we get it done.

We adore technology and advancement!

I mean, there is probably no surprise there, but we love to surround ourselves with the latest technological advances – be it about our physical surroundig, or our codebase. So we research, we read, we learn. We get familiar with new frameworks, libraries, advanced solutions every day – then apply our newly acquired knowledge in your software, making it better, stronger, faster, safer.

How do you recognize a good developer?

Now this can be hard – as a person not knowing anything about software development, how can you tell, who will be the professional skilled enough to get the job done?

The good news is, you don’t need technical knowledge to make that decision. Good professionals stand out. Not by having millions of frameworks listed in their CV-s, not by having multiple years of experience – although that is not a bad thing –, not by asseverating they are the best, or the only ones who have a solution for you.

Good professionals stand out, because they are enthusiastic and passionate. They simply love what they are doing, they are able to switch to problem solving mode, and even start braimstorming with you to enhance your ideas as soon as they understood your needs. They are perfectionists, simply because they want to be proud of their making, and give it the best they can think of.

„Okay, but what about the sneak peek?”

And yes, here we are, after all this talk about what developers are not doing, let’s see how we at Cuurios actually turn your idea into software, so next time you work with a programmer, you will have a better understanding of what we really do [1].

  • Driven by curiosity we listen carefully what you want and challenge what you need.
  • We read the documentation, getting a nice, overall picture of what you need.
  • We read the documentation again, going into details, stop here and there for a second, making notes.
  • We just sit and stare. Now this might look like we are not doing anything, just staring out of the window, waiting for the day to end, but this is the part where at least 20% of the work gets done. We write and design the whole application in our head, tracing our steps, making mental or actual notes, connections, stripping the whole use case down to logic, numbers, actions, and finally breaking it down to parts.
  • We read the documentation again. I know, by now we should know by heart, right? But at this point, we make notes, create diagrams, start researching for the best solution, the latest technologies, the most useful libraries.
  • Brainstorm. Yes, programmers rarely work completely alone. We use our colleagues recommendations on solving similar problems they encountered, share our experience, and learn from eachother. Even if this happens online.
  • Depending on the duration of a project, we prepare the sprints, or the first couple weeks at least, read the documentation one last time (I know, right?), include every little detail in tickets, organize the workflow, then get started with the typing all day...

From here on out, we do the same routine every day – although it’s never the same and never gets boring:

  • In the morning, we prepare for the day. We go through what we finished the day before, decide on and preapre for the next steps.
  • A daily scrum meeting keeps us accountable – also a very good place to see if someone got stuck, needs help, or just a different approach or idea to get out of a deadlock.
  • During the day: design, research, code, test, debug, finalize, repeat. For each and every small part of the application, until we get a result we would proudly present.

Good software developers take pride in their work. They don’t just enjoy creating solutions for you, they are just as happy – if not even prouder and happier – as you are, when you start using what they made for you.

[1] The working method described here is Cuurios-specific, other companies and teams may have different ways to divide tasks and manage their workflow.

Do you recognize the value of your data?

Every company works with data. Productivity, prices, stock, you name it, anything that makes its way to the next report and helps you take the next step – just numbers. Chosen the right strategy, you can make these numbers work for you.

A case from the trenches

We dedicated the previous blog post to the value and importance of your data. You might already be intrigued to imagine how those numbers can save you a lot of work and even make your company more successful or “just” simplify your decision making process. It’s time to do something about it.

But then what? It might be very tempting to go for the new and shiny, to start an Artificial Intelligence (AI) project because that is the future and you are afraid to miss the boat. But AI requires a very high digitization maturity and work best on very specific use cases.

The technology has some known drawbacks, requiring large amount of (mostly labeled) data. It also lacks in so important auditability, a real and valid concern for many business leaders.

Focusing on this far-way horizon may lead you to over-reaching, over-spending, and might actually backfire. Lacking in tangible results to show, it could reduce the willingness to invest in data and data technologies. You will miss the low hanging fruit that will add value to your business and will help champion data in your organization.

Through a real use case at one of our customers, I will try to explain how we managed to integrate data and create value by integrating a use case that mattered.

The use case

This customer is responsible for the operations of multiple industrial sites, each producing 24/7. At the beginning of the day, engineers gather data, calculate, and analyze the shortfalls in production from the day before. What was the reason, was it planned, what can be done about it, will this impact our overall production, etc.

This data needs to be revised and approved by the operational and reporting team and reported officially to management.

Until very recently, they would extract data from their process data historian, process it through an excel sheet and pretty much run the process by hand using the Microsoft Excel.

A repetitive and error prone process, with little value in the data wrangling. A perfect candidate for automation!

To support this customer, we deployed a solution that would:

  • Fetch the data automatically from the OSIsoft PI data historian
  • Run an algorithm to detect production shortfalls and faulty input. The algorithm tries as well to infer the cause of the production shortfalls from previous related cases.
  • Present the results in a Web UI, including history and raw data
  • Present the detected production shortfalls to engineers and operators for analysis and validation
  • Extract the results into the right format for exporting to the reporting system

Data is about your business, not just technology and algorithms

Nowadays data is everywhere. It is the hot topic of the moment, for businesses and in the general public. There are heated debates in politics about “Data”, data wars, and even a new science entirely dedicated to data!

When it comes to data, you might be wondering, should you build an enterprise architecture with data as your starting point (data-centric)? Or build a data structure around the existing landscape (data-driven)? What about data lakes? Do we actually have any data?

Well, tackling data is highly dependent on the specific configuration of your organization history, business, and IT landscape. 

At Cuurios we believe that Data should be CENTRAL to your organization. Gathering, managing, and acting on your data is your core business. But there are no one-size-fit-all solutions. Data is a mindset, the most important is to just do it, however small the first steps might be.

In this blog post I am giving some insights on how we see Data at Cuurios and sketching the first steps towards data proficiency!

DATA

It sometimes feels like data is something new, something very hot, the core of the 21st century technological battlefield. But data has been there for a long time! Measuring, gathering and analyzing data is at the core of the scientific and industrial revolution. Without Galileo gathering data on the moons of Jupiter with his telescope, there would have been no proof that Copernicus was right, and we might still be thinking that the earth is at the center of the universe.

Data is not a thing, a disincarnated entity that exists for and of itself. Data is grounded in reality, it is information that represents assets, people, events in the real world. Data is what makes large-scale organizations possible. Without data, how would you know what the state of you inventory is without having to recount every time? What the state of a critical asset is without having to look at it?

The first form of writing ever discovered, the Sumerian tablets [1], were accounting records of production and exchanges of goods, i.e. data.

What has changed to make data the focus of a new gold rush? 

  • Storage capacity has increased exponentially. When a Sumerian scribe needed hours to imprint a clay table, we can now record terabytes of data for very little cost.
  • The internet (as in the complete networking infrastructure). No need to have people do the measurements and record the data themselves. Everything is be automated.
  • Advanced in computer power has made the application of advanced AI algorithms cheap and rewarding.

This list describes techniques to store, manipulate, and analyze data.

What it does not describe, is a change in the nature of data. People tend to concentrate on the new hype, assimilate data with data science, and equate analysis with machine learning. This is a very narrow view of what data is and limits its usefulness to a few very advanced use cases.

Because first and foremost, data is information, information about your business, its customers, its assets, its financial state. It represents the tangible and is often the only thing you have to steer large complex organizations.

We think that data should play a core role in every organization, be CENTRAL to decision making and action taking. Without data, any decision taken is an educated guess. 

THERE IS MORE DATA AROUND THAN YOU THINK

In practice, we often encounter organizations that claim not to have any data. Because they don’t have a data lake.

The first thing they have on their data roadmap then, is to create one. But really, a data lake is just a big database. It won’t tell you what to do with your data. In our experience, many organizations, after having spent an incredible amount of time and budget on creating a data lake, are stuck. They don’t know what to do with it.

Because your data is about your business, not technology, not algorithms.

What we usually see is that organizations already have data, very often plenty of data, scattered around, in custom made applications, asset databases, excel sheets. Because you can’t function without data.

What they lack is an approach, a concrete process to manage data, to embed it in its day to day operations. The data processing, the algorithms, should come in support of operations.

Making sure data is part of your operations day to day business, that is being data-centric.

In order to do that, you need to reverse the data analysis process, look at your data from a business perspective:

  • What are my most important use cases, processes, assets?
  • Which data do I have about them? Where can it be found, in which format? Do I need more of it?
  • How can we automate this specific use case? Which algorithm can be used? 

At Cuurios, we have extensive experience working in the industrial sector. In most Industrial settings, processes will already be described. They will be backed by data for real-time monitoring, stored in a historian. Optimization and analysis algorithms are known.

The actual running of the algorithms, the analysis of the data and the generation of advices is traditionally a step performed by engineers, in Excel, Matlab or others. Tools great for exploration and scientific inquiry, but not made for automation.

For most companies, there is tremendous value to be added by connecting data sources to each other and automating their analysis. Actions can be defined and set-out quicker, with a better response to issues and a higher efficiency.


[1] https://www.cam.ac.uk/research/news/a-stray-sumerian-tablet-unravelling-the-story-behind-cambridge-university-librarys-oldest-written


HOW TO: achieve a performance boost with the PI Web API

At Cuurios we are keen to develop software solutions that use your process data to deliver valuable insights. The OSIsoft PI Asset Frameworks (PI AF) provides a hierarchical, asset centric model of data with detailed history, which is indispensable to monitor and further analyse vital production data in the industry. It means millions of records of real-time and historical data. This data is invaluable, provides not only useful insight but also the possibility of improvement for better control and efficiency when processed and displayed right.

Have you chosen wisely?
Having a database filled with vital information is not more than a pile of values, up until the moment when you put that data to work. Every number, every date, every remark can be useless or on the contrary: it should help your company to work smarter, not harder.
Making the right connections, creating useful relations, calculations and transforming your data into concrete actions is what our motto, data to action means. Poor choice of data to process means poor, sometimes even useless insights. Modern technology provides you the tools, to make your company’s job easier – an overflow of data on the other hand will just make everyone’s life harder.

Let’s get technical
During our several encounter with PI AF (using the Web API) we learned some useful lessons and tricks. For those with an IT experience, the fact that the extended use of a framework also means dealing with its limitations and shortcomings is not all too surprising. In case of the PI AF, the main obstacles we had to overcome were related to the limit of search queries, result sets, and performance issues due to the excessive amount of information.

The use-case
One of our use cases were monitoring and handling inhibition values on offshore gas production platforms – more precisely detecting when an inhibition for any checkpoint is turned on, and track it’s changes until it is turned off. The added value lies in a well-managed and monitored safety system.

Finding the PI points
These checkpoints do not just belong to one asset or even one asset type, in fact, they can be found all over the asset tree. This is where the PI AF built in search query comes to the rescue.

https://MyServer/piwebapi/search/query?q=name:*INHIB

The above query gives us almost 6.000 results. Although PI AF has the possibility to set the size of the result set, the built in maximum limit is 1.000 item per page, which means a minimum of 5 REST  requests in parallel to process the almost six thousand items.
What makes it complicated to work with PI AF at the very beginning is the fact, that the above query does not provide us values, or any actual data about the PI point other than it’s  WebID, the unique identifier used in PI AF. As a next step, querying the WebID gives you direct access to the actual values of a certain checkpoint.

Performance with over 6.000 REST request?
Although now we have all the inhibitions points directly accessible with their unique WebID, the reality is, checking all of their values takes roughly six thousand get requests. If you can’t imagine what that exactly means, below an example:

https://MyServer/piwebapi/streams/yourWebID/value

6.000 of these requests need to be sent and processed. It takes in our particular setup over 5 minutes. Can you imagine pressing a button and waiting for over 5 minutes for the result? Let’s all just be honest – the reality is, most people lose their patience even after a couple of seconds, because even that loading time is unacceptable nowadays, let alone 5+ minutes.

Let’s build stream sets!
Implementing a working Refresh button at this point was the last straw. While the updates where running only hourly in the background, this 5 minutes wasn’t great, but still barely noticeable from a user point of view. Up to the point, when we placed a button on the page for manual refresh purposes. Then it became clear: we need another solution.
After some research we found out, that the PI AF Web API supports bulk data retrieval even for unrelated pi points, the only thing you need is the list of WebID’s. These queries are called stream sets and are providing fast bulk retrieval. 

https://MyServer/piwebapi/streamsets/value?webid=yourWebID1&webid=yourWebID2

Only a couple of things to keep in mind:

  • the URL has a length limit, in our particular setup we could retrieve the values for approximately 400 WebID’s in one stream set (the length of the webids varies, make sure you test this extensively in your setup);
  • it is necessary to adjust your method to handle the response accordingly, as the result is a list of json objects called Items,
  • if any of the WebID’s in the stream set runs on error, the whole request runs on error, meaning even one unavailable WebID and the whole request goes down the drain.
  • Implementing stream sets meant we could reduce the number of REST request from 6.000 to 15. Additionally, a stream set request response time is not noticeably longer than a simple value request, so our performance got a big boost: from over 5 minutes down to an average of 10 to 15 seconds. 

Summary
Building something really meaningful on top of a database with literally millions of available records, if done smart, can improve the way you organize your work. Focusing on what you need to know, what you need to see from those information at first blink means you can put the carefully collected data to work. It is not going to make the decisions for you, but it can help pointing out when and where you need to make decisions, take actions.

blog

Clients

total
sabic
fluxys
isover
IV-infra
next2
translink
clients

References

I have been working with Cuurios for more than two years now on behalf of Total E&P Netherlands. One key benefit we found working with Cuurios is their approach: centered on our needs, developing solutions to work more efficiently and finding solutions to problems. They work fast, properly and are always responding quickly to requests or troubleshooting. The work they deliver is of top quality and we use all the tools they built on a daily basis throughout our whole organization. Their main solutions provide operational insights based on automated analysis of our production data. Keep up the good work!

Elie Feghali
Digital Officer

From our side, what we would like to say is that our experience with Cuurios is one where they were quickly able to understand our needs and talk our language. Cuurios provided a fresh and different approach to our way of solving challenges.

Francisco Pérez
Lead Scientist

Having worked with Cuurios a couple of years now, they continue to surprise me, in a positive way that is! Their core strength is to really capture what their client requires/desires and translate that into a sustainable solution. Whether it’s a digital operations logbook, a cloud based global portal or an operational planning tool, Cuurios will deliver. Their flexible mindset and focus on solving issues when they arise (instead of spending the same amount of time bickering) is something which I very much appreciate.

Franc Boverhof
Program lead collaborative environments

The collaboration with Leen de Graaf has proved very valuable to us. The combination of business thinking, technical knowledge, but also a sense of stakeholder management always results in actual impact!

Roy van den Berg
Project manager data services

We met Cuurios through Microsoft. From this moment, it was clear to me just how driven they are and that they really know what they’re talking about. At breakneck speed, they immersed themselves in our query and immediately considered various possible constructive solutions. They were also quite capable in facilitating our first steps in the area of machine learning. They took the time to explain to us the basic principles. This made us feel confident that machine learning is a suitable solution to our problem. Besides their technical knowledge, I felt a real connection between us which made the collaboration even more pleasant. Working with Cuurios was the right decision. That’s for sure.

Joost Assendelft
Teamleader Geodata

references

Are you Cuurios?

Are you an inquisitive (curious) software professional and do you think it would be cool to work for an international software start-up? If so, we invite you to tell us more about yourself.

Do you want to get in touch to see how we can help you? Please call us or send an email.

+31(0)85 0608400
info@cuurios.com

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