How did STACC help Selver make Supply Chain Management more efficient?
The advances in information technology allow people to develop accurate machine learning models that can learn from collected data. The application of such models helps to predict the demand for various products, such as goods sold in grocery stores. Retail chains sell a wide range of products which are ordered using different algorithms. One of
How did a physicist become a data scientist?
In spring 2019, I was finishing up my bachelor studies at the physics institute of Tartu University. At the time, I was trying to figure out my next steps in life. I had a short-term plan assigned to me by the Estonian Defense Forces – 11 months of military service, but I lacked a longer
From University to Personalized Medicine Internship and on to Data Engineer
It was a warm summer night when I decided to submit my candidacy for an internship position in STACC, and voilà, a few weeks later I got an answer saying they had just returned from summer vacation and were open to talk. I was a fresh graduate of Computer Science and planned to continue my
From an English Teacher to a Data Science Project Manager!
Following the example of my mother and both grandmothers, I was convinced from a very young age that I would one day become a teacher. After my bachelor’s studies, I planned to start my master’s studies in one of the curricula of teacher training at the University of Tartu. Friends who were working as teachers
How did STACC help the National Heritage Board to estimate the stability of museum objects using artificial intelligence?
Did you know that artificial intelligence can also be used in museums? The Estonian National Heritage Board launched an exciting project called kratt Sälli* whose purpose is to make conducting inventories in museums quicker and more convenient. Due to the large amount of museum objects, it is not feasible for museum staff to thoroughly examine
The best machine learning service provider for Estonian startup companies – get funded!
Our portfolio contains successful data science and ML projects with many Estonian startups: FoodDocs, E-Agronom, Eurora Solutions, Messente Communications, Balti Meediamonitooringu Grupp, Mifundo, MS Skype, Zeroturnaround, Reach-U, Wise, Plumbr, KappaZeta, Texta. STACC has enhanced the core technology of these companies with ML and data analytics capabilities. It is not just the superb technology we provide, but we
AI creates plays: How did STACC make robots to write, and act plays inspired by Chekhov?
Did you know that robots aren’t just made for scrubbing the floors and other types of dirty work? They can be used to do lots of other exciting things, like theatre. To break the cult of robots scrubbing floors and mowing lawns, MEDITA researcher Liina Keevallik took it upon herself to do something particularly cultural and beautiful with robots – robot theatre.
Do you want to know which bird is singing outdoors? Lapponica – bird song identification app will help you!
Have you ever heard a bird sing while walking in the park or in the woods and wondered which bird sings so beautifully? STACC and Lapponica have developed a powerful bird song recognition application that allows you to record a bird song and identify which bird the song belongs to. Lapponica is a company created
STACC is looking for an excellent Data Engineer Team Lead
Data Engineer Team Lead STACC is the leading data science company in Estonia that develops machine learning models, artificial intelligence, and data analytics solutions. As a Data Engineer Team Lead, you will oversee a small group of engineers, which is responsible for STACC´s day-to-day smooth data flow and support of the data scientists team. You
STACC Recommender System through the lens of architecture
Activities 2016-2017 STACC built the first recommender system back in 2016. It was an e-mail recommender that was built to help create campaign e-mails by generating personalized recommendations from a selection of campaign products. You can read more about STACC recommender systems from here. Recommender system The central interaction point with the system is the