Marple haalt half miljoen euro op om ingenieurs razendsnel inzicht te geven in hun data.
ANTWERPSE TECH-STARTUP MARPLE HAALT HALF MILJOEN OP
De Antwerpse tech-start-up Marple heeft in een tweede investeringsronde 500.000 euro aan groeikapitaal opgehaald. De investeringsronde was gevuld na minder dan 1 maand door een gezonde interesse bij private investeerders. Ook Imec en VLAIO namen deel aan de investeringsronde. Het verse kapitaal moet Marple helpen het team uit te breiden en verder aansluiting te vinden op de markt van software voor R&D ingenieurs.
Marple helpt ingenieurs innoveren dankzij slimme software die data verwerkt en analyseert. “We zetten daarbij onder andere in op het snel en vlekkeloos omzetten van grote bestanden meetdata in glasheldere grafieken.” zegt Matthias Baert, een van de oprichters van Marple.
Idee vanuit de Formule 1
De twee oprichters van Marple zijn beide zelf ingenieurs. Zij stelden vast dat de software waarmee test- en controle-ingenieurs het op dit moment moeten doen, vaak de wensen overlaat.
Matthias draaide in het 2017 en 2018 seizoen mee als ingenieur bij het Formule 1 team van Mercedes. Hij stelde vast dat zelfs binnen de Formule 1, waar je de meest innovatieve tools zou verwachten, het aan goede software ontbrak om de data die van de wagens wordt verzameld efficiënt te organiseren en analyseren. “Dit was voor ons het signaal dat er nood is aan een betere oplossing”, zegt Matthias.
Door het databos de bomen zien
Productontwikkeling en productinnovatie worden in grote mate gestuwd door de ideeën en inzichten van ingenieurs. Met de laatste ontwikkelingen op vlak van sensoren en meetapparatuur kunnen ingenieurs grote hoeveelheden aan data te verzamelen.
“Tijdens een test levert elke milliseconde enorme hoeveelheden data op”, zeg Nero, mede-oprichter. “Dat is heel leuk voor de ingenieur, maar de uitdaging wordt dan om door het bos de bomen te blijven zien. Marple wil dat probleem aanpakken.”
Marple legt zich toe op drie elementen van het werkproces van de ingenieur: data management, data visualisatie en het verwerken van big data. De combinatie van de drie maakt Marple enorm krachtig.
AI, Machine Learning en Big Data?
Marple is voorzichtig op de vraag of hun software als AI moet worden gecatalogiseerd. "Uiteraard liggen verschillende slimme algoritmes aan de basis van wat we doen. Maar onze focus ligt in de eerste plaats op ingenieurs weer controle te geven op hun data, alvorens ons toe te leggen op het automatiseren met AI", aldus Matthias.
Wat gaat Marple doen met het nieuwe kapitaal?
Het verse groeikapitaal laat Marple toe in de eerste plaats zijn team uit te breiden, zowel aan de technische als aan de verkoop kant. De markt, vooral R&D, product ontwikkeling en labo-omgevingen, is zeer internationaal. Marple’s eerste klanten komen niet alleen uit België, maar ook uit Nederland en Duitsland. En daar stopt het niet “Ook in bijvoorbeeld Scandinavische landen merken we dat de markt groot is”, aldus Nero.
Marple werd opgericht in 2020 door Nero Vanbiervliet en Matthias Baert, en werd groot onder de vleugels van het imec.istart incubatieprogramma. Intussen heeft Marple zijn team verdubbeld, en willen ze de funding gebruiken om het product verder uit te werken en tegelijk zo goed mogelijk op de markt te plaatsen.
Marple raises half a million euro to give engineers lightning-fast insight into their data
ANTWERP TECH START-UP MARPLE RAISES HALF A MILLION EUROS
Antwerp-based tech start-up Marple has raised 500,000 euros in growth capital in a second investment round. The investment round was filled after less than one month due to healthy interest from private investors. Imec and VLAIO also participated in the investment round. The fresh capital will help Marple expand its team and further connect with the software market for R&D engineers.
Marple helps engineers innovate with smart software that processes and analyses data. "We focus on, among other things, the rapid and flawless conversion of large files of measurement data into crystal-clear graphs" says Matthias Baert, one of the founders of Marple.
Idea from Formula 1
The two founders of Marple are both engineers themselves. They noted that the software with which test and control engineers currently have to make do often leaves much to be desired.
Matthias worked as an engineer for the Mercedes Formula 1 team in the 2017 and 2018 seasons. He found that even within Formula 1, where cutting-edge technology is being developed, there was a lack of good software to efficiently organise and analyse the data collected from the cars. "This was the signal for us that there is a need for a better solution" says Matthias.
Missing the data forest through the trees
Product development and product innovation are largely driven by the ideas and insights of engineers. With the latest developments in sensors and measuring equipment, engineers can collect massive amounts of data.
"During a test, every millisecond generates enormous amounts of data" says Nero, co-founder. "That's great for the engineer, but the challenge then becomes to not miss the forest through the trees. Marple aims to address that problem."
Marple focuses on three elements of the engineer's work process: data management, data visualisation and big data processing. The combination of the three makes Marple immensely powerful.
AI, Machine Learning and Big Data?
Marple is cautious on whether their software should be catalogued as AI. "Of course, various smart algorithms are the foundation of what we do. But our focus is primarily on giving engineers control over their data again, before focusing on automation with AI," says Matthias.
What will Marple do with the new capital?
The fresh growth capital allows Marple to primarily expand its team, both on the technical and on the sales side. The market, especially R&D, product development and lab environments, is very international. Marple's first customers come not only from Belgium, but also from the Netherlands and Germany. And it doesn't stop there. "Also in for example Scandinavian countries we notice that there is a large market", Nero says.
Marple was founded in 2020 by Nero Vanbiervliet and Matthias Baert, and grew under the wings of the imec.istart incubation programme. In the meantime, Marple has more than doubled its team, and they want to use the funding to develop the product further and at the same time place it as well as possible on the market.
Welcome again fellow Marpleans!
If you remember what we said a couple a couple of blogs ago we are supporting the Formula Student Team Delft (FSTD) with a sponsorship (aren't we generous)! For those who don't know, Formula Student is a worldwide competition for students to build and race their own electric race car.
Because the collaboration is such a succes we decided to make the trip from Antwerp to Delft and check out their workflow and show other Marpleans how cool it is to work with Marple.
It all starts with a good set-up. You want a high frequency logger in order to extract enough data and really get the finest details of your configuration. The FSTD boys and girls go above and beyond to achieve this. Even if this results in taping a laptop on top of the car. The basic logger in the car only logs at 250 Hz and to test the motorcontroller they needed at least an 8kHz logger.
Safety jackets on, let's go! Look, I know you're here for data and data analysis but I won't deprive you of this cool driving footage either. The test in question was so they could finetune the motorcontroller. This means driving around some cones on the parking lot was enough!
Then what? I'll let Andrea, the George Clooney of control systems tell you himself:
Data visualisation in Marple.. Oh What A Dream! It took more time walking to the office than having the datasets in Marple. In fact, because they work with our infamous API, as soon as his laptop connected to the internet. The upload of the dataset to the Marple data management system started and there was no waiting time for them to start analysing the data. I say them because as you know Marple allows your whole team to simultaneously look at the data.
After quickly finding the possible improvements, they made a couple of tweaks and went to the track.
Good times in Delft!
That's it from us, hope you enjoyed it. If you want to know more about the use case please contact us about it!
The Marple team
We're back with another blog post, this time on your request!
Two weeks ago we asked you what kind of data you wanted us to visualise with Marple.
Cycling came out as a clear winner. Convenient! We had already planned to kick-off the Marple summer in Spain for a work-from-where-the-sun-shines week. Now we had an excuse to also bring our bikes.
![A Marple meeting in the pool](marple_meeting_pool.jpg)
(Marple working from where the sun shines)
The main reason we cycle is obviously to impress our friends and ex-girlfriends on Strava. Kidding not kidding, [Strava](https://www.strava.com/about#:~:text=Strava%20is%20Swedish%20for%20%E2%80%9Cstrive,they%20love%20even%20more%20fun.)
is a cool application to gain insights in your ride data and compare it with friends.
Strava also estimates the average power output of your ride in watts. This is an ambitious estimate, because next to speed, weight and road gradient (values Strava typically knows), there are multiple other variables that influence power that Strava does not have information about. Think about weather conditions, the aerodynamics of your bike position, whether you are drafting behind your friends (yeah you, Matthias), etc.
As Strava's estimated power output has been at the heart of quite a few discussions within our team before, we decided to put this estimate to a test.
We planned a route, rode our bikes, and [uploaded the ride to Strava](https://www.strava.com/activities/5627688712).
![The Marple Strava Ride](marple_strava_ride.jpg)
Idris rode the ride with a standard power-meter. Before uploading the ride to Strava, however, we cut the power data from the file.
Then we uploaded the ride data (without the power data) to Strava. Second, we fetched Strava's estimates of Idris' power output from Strava (we found this data easily in JSON-format in the Network section of the developer tools of our browser).
After converting this data to csv-file format (using a plain and simple custom python script), 99% of the work was done. In the blink of an eye, Marple parsed the csv-file to its databases and in one click we immediately had a very clear view of how the actual power output compared to Strava's estimation.
Setting both metrics to the same scale shows that Strava's estimation is doing a pretty impressive job.
We noticed that Strava's estimated power output is quite noisy. No problem for Marple. With a click on a button, we applied a moving-average to
this data, creating a signal that tells a much clearer story.
By organising our data in different workbooks, and adding different metrics to those workbooks, we gain further insights under the hood of our data.
For instance, we noticed that when the gradient increases, Strava mostly underestimates the actual power output. The other way around, downhill Strava mostly overestimates the power output. As these two tendencies cancel each other out in a roundtrip as ours, Strava's overall estimate is still pretty accurate.
Are there any insights we are missing?
WIth love from Spain,
The Marple crew
Hola los Marple aficionados!
We at Marple like fast cars. More so, we love the engineers who design them!
That's why we're really excited to announce that Marple is working together with the beautiful students of the Formula Student Team Delft (FSTD).
FSTD is designing an electric race car from scratch. Yes, that's as cool as it sounds!
They hope to collect prizes this summer at prestigious racing events in the Netherlands and Germany. Marple helps them to get on top of their test data, showing (visualising!) them the way to an efficient design process and hopefully victory in the races they are participating in.
True Marple insiders will know that Marple's founder and chief MBaerto used to be a member of the FSTD racing team when he was a student in Delft. This makes this collaboration even more special.
Are you also designing an electric race car from scratch?Or building something else Marple sounds useful for?
Make sure to reach out!
Much love a todos,
The Marple team
We want to share some awesome news with you! We were very very excited that we were selected for the Quick Wins subsidy of POM this week! This will allow us to work together with Dana & Hardt Hyperloop in the form of a pilot. We are extremely happy about how we are able to make time series data analysis for the engineers in those two companies way more fun & efficient!
POM West-Flanders is a government agency supporting private companies to innovate and collaborate with startups such as Marple. This collaboration is a big validation of our conceptual idea that data analysis can be made more exciting!
Working together with Dana and with Hardt Hyperloop is a big deal!
Dana is making drive trains for vehicles (for example: hybrid cars) and during the development of those vehicles, tests are being done to make sure that everything on the new design works before going in production. Dana engineers will be able to analyse their test data in Marple which will allow them to clearly and easily see what goes on, on the test-bench!
At Hardt Hyperloop, we will be able to be part of the next forward jump in passenger transportation. This project is so much in line with what we believe in! Specifically the fact that engineers are the cornerstone of progress makes us very committed to support the Hardt Hyperloop engineers.
Thanks for reading!
The Marple team.
We have some exciting news again, this time about our product. We are moving from a desktop solution to a server based solution and make Marple a web tool.
A server based approach has many benefits:
We will soon launch a demo version online so you can experience the advantages Marple brings. For now, enjoy the short demo video below:
Do you want more information about our server product? Make sure to reach out!
The Marple team.
We've had a busy couple of months since our last blog post. In this post we want to give you an update on two elements: our second test period and our first summer interns. Let's go!
We've had a very successful second test period in May-June with more than 100 users testing our tool and providing valuable feedback. In total almost one hundred billion data points were analyzed by Marple during this period. That's amazing. We've seen new use cases that we find very interesting and open a new range of opportunities. We're currently brainstorming about our product to see if we can capitalize on these opportunities. But more on that in our next blog post.
Our team is expanding! Since the beginning of July we've had Flor and Liesbeth joining our team as summer interns as part of their study. Flor is improving the data handling of Marple by adding support for more data types as well as improving the internal data structure. Liesbeth is researching how we can improve on our current data subsampling techniques. They've only recently joined our team but are already making valuable contributions to Marple. It's great to have some extra (wo)man power in our team!
Of course, a team is only a team once there is a team photo, so we lined up on a nice piece of grass.
Cheers and see you next time!
Matthias & Nero
PS: Mandatory jumping picture as a bonus (Flor almost went into orbit on this particular attempt)
We are very happy to announce that Marple has joined the imec.istart accelerator programme! Imec.istart is a startup accelerator in Belgium with a focus on tech startups. Therefore, it is a perfect fit for our company. The accelerator is a branch of IMEC, a renowned research center with a focus on microelectronics.
Imec.istart will support us in various ways including funding, coaching & mentoring, workshops and access to its large network. To top it off, we will be moving our offices to a co-working space in Antwerp. We look forward to joining a community of fellow startups when the corona dust has settled down.
Matthias & Nero
It's been a while since our first post, but a lot has happened since.
Our pilot testing phase has officially kicked off! The first version of Marple is now ready and is being tested by various pilot testers. We already gathered feedback from them about what parts they really like, what features they are missing... and a bug once in a while. It's super cool to see how Marple is being used by the pilots and we can already notice that Marple is providing new insights in their data.
We've also put some time in the business side of things. We practiced our pitching skills and had a deeper dive into our marketing plan and strategy. In the coming weeks we will give our website an upgrade. Not only did a lot change over the last months, but we will provide more content about our startup and the product on our website.
Lastly, we have some exciting news. However, we'll leave that for the next blog post once we can tell you every detail about it! But we'll give you one key word for now: business accelerator (oh that was two words...)
See you on the next blog update!
Matthias & Nero
Welcome to the first post of Marple! I must say, it's quite exciting making a first post. In this post we would like to give you an update on our progress, challenges we are facing, our current planning and our vision on future blog posts.
In the last two and a half months we have been very busy with the technical development of our product. So far we are on schedule with our initial planning. We already managed to use our tool on some actual real-life data and perform some analysis on it. We were very happy to see that our tool is already showing its potential. Being ahead of schedule meant that we had some time to work on marketing. We made a nice and shiny new website that we are really happy about. Make sure to check it out at https://getmarple.io/.
We had good Christmas and New Year celebrations and are ready to start on the final development of our tool where we will add more features that make Marple even better. In February we will do a first test with 20 confirmed pilots. They will use our product and give feedback on what they miss or would like to see different. We can always use more pilots, so if you think the tool fits your needs and you would like to give it a go, please let us know!
We are planning to make more blog posts in the future. Some of the blog post will be progress updates, like this one is, but we will also make more technical posts about data processing, data handling or other topics we like to share with you. So stay tuned!
Don't hesitate to reach out to us if you have any questions.
Happy 2020 from the Marple team.
Nero & Matthias