Ukrainian IT company with focus to data science

Ukrainian IT company with a focus on data science solutions.

We have a lot of experience in computer vision, neural networks, machine learning.

We also work with big data and IoT, integrating data with analytical tools and solutions.  

We use Java and Python stacks for development.

Our domain expertise includes AdTech, FinTech, infrastructure, healthcare, security, smart city, entertainment and sport.

$25 - $49 / hr
10 - 49
Show all +
Kharkiv, Ukraine


Key clients: 

USA and European IT companies and startups which use or plan to use data science to keep on top of the innovation curve.

Rubicon,, Worldsensing, FirstImpression and other companies chose Quantum as a strategical partner.

Rubicon Project Guaranteed orders support and enhancement

The work in the mixed team (in house and outsourcing) for reliable business support.

See the demo.


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Java Development for Data Analytics Platform

"Their professionalism and ability to meet all of our specifications was exceptional."

Willing to refer: 
The Project
Mar. 2017 - Ongoing
Project summary: 

Using Java, Quantum created a two–stage process that interacted with Amazon Elastic MapReduce (EMR) and Hadoop clusters to assess raw data on user ad interaction and provide big data analytics.

The Reviewer
11-50 Employees
Tel Aviv, Israel
Systems Architect, Tech Company
The Review
Feedback summary: 

Quantum’s expertise helped to increase understanding of big data analytics and user traffic. They were quick to respond with fixes in spite of their work–week being offset by one day. While meetings were occasionally difficult to set–up, the project finished on time and within scope.


Introduce your business and what you do there.

I am a systems architect and integrator for an ad product creation and monetization platform.


What challenge were you trying to address with Quantum?

We needed help breaking into big data analytics so that we could assess the different amount of traffic our ads produced. We were looking for new and interesting insights into the advanced statistics of how users interact with ads for our clients. To do this, Quantum built us a pipeline for big data processing.


What was the scope of their involvement?

I went to Quantum with a general vision of how the platform should be built based on my own research on how big data analytics platforms usually work and their architecture. I initially discussed this with Quantum’s solutions architect, and as we got into more project details, I was in contact with two Java programmers. They developed a two–stage program in the Amazon EMR to process big data across a Hadoop environment. What they wrote analyzes static raw data in Amazon’s S3 storage on a regular schedule, which we then evaluate in our internal statistics system.

What is the team composition?

Our first contact was with a representative and after that our main points of contact were an infrastructure technician and the general programmer. As needed, I also reached out to Quantum’s Solutions Architect and multiple Java programmers with project details.

How did you come to work with Quantum?

They were suggested to me by a previous colleague who said they were extremely knowledgeable, especially when it came to things in the vein of machine learning and data processing. We were impressed with their successes and they had the benefits of being in the same time–zone and speaking the same language with me. 

What is the status of this engagement?

We began working with them March 2017 and the work is ongoing.


What evidence can you share that demonstrates the impact of the engagement?

We now have our own internal statistics system that is similar to Google Analytics but with access to very low–level statistical reports. We can analyze the behavior of users on different websites and how they engage with our ad placement. We had very few problems throughout the entire project and anything we found Quantum quickly fixed.

How did Quantum perform from a project management standpoint?

We generally used email to communicate and I would set up Skype calls to meet with specialists and their programmers. Even though we are in the same time–zone, our weekends begin on different days but that rarely presented any problems.

What did you find most impressive about them?

We came into this project without any experience processing big data. They were willing to work with us and help make sure we gained that experience. Their professionalism and ability to meet all of our specifications was exceptional.

Are there any areas they could improve?

There’s nothing I could point out. They are very experienced and met all of our expectations.

Do you have any advice for potential customers?

We came to them with the project outlined and detailed specifications, because of that everything went as expected. Potential customers should have a good plan for a large block of consecutive work so that Quantum can allocate their resources and provide the best scheduling. 

Overall Score
  • 4.0 Scheduling
    It could be difficult to schedule meetings but aside from that, everything went smoothly.
  • N/A Cost
    Value / within estimates
  • 5.0 Quality
    Service & deliverables
  • 5.0 NPS
    Willing to refer