Stay ahead. Make better decisions with your data and our experience.

We build smarter solutions for business problems. We are a Machine Learning service provider that helps companies reduce costs, save time, automate operations, increase productivity, and boost efficiency and effectiveness.

Data is growing faster than ever before. Nowadays, about 1.7 megabytes of new information will be created for every human being each second. This amount of data cannot be processed using traditional methods.

Machine Learning has already matured to the point where it should be a vital part of any organization’s strategic planning. It also has transformed today’s businesses, making them realize the real power of getting meaningful insights from data. However, few are fully prepared or have the necessary skills to take advantage of Machine Learning potential.


Machine Learning solves complicated real world tasks in a scalable way.

As a Machine Learning consulting company, we advise you on the best approach if you detect a need that can be addressed with a Machine Learning project.

Some viable applications of Machine Learning that our Data Science Team has expertise in working on are:

  • Recommendation Systems
  • Patterns Recognition
  • Behavior Forecasting
  • Data Clustering

As part of the Machine Learning process, we take care of the entire project development — from determining requirements to delivering a complete solution.

The following flow describes how Vybrant can accompany your business throughout the Machine Learning project.

graphic of machine learning process at Hexacta

    1. Collect. Everything starts with data gathering because, without it, we will not be able to see new opportunities. Our Data Scientists relay this task to our Data Engineering team, giving them broad ideas on what they want to capture in order to create new insights. This step defines the on-boarding Data Flow.
    2. Enrich. We all know that data by itself means nothing, so Data Scientists, Data Analysts, and Data Engineers work together to add context to new data. This is the Data Transformation Layer, where these new records are organized to be meaningful to different users or applications.
    3. Report. By organizing data, we are now able to start working on extracting information, and we are starting to look at the past for reasons about what we have today. This step is business-related because here is where you can enable the ability to track KPIs and OKR.
    4. Serve. Once data is organized and tracked, you can start working on the present and providing data to end-users so they can contribute more context to your data. In this step, you can start thinking about what your organization foresees now that you understand the past and work in the present. You can trust in using your data to start working on what to expect from the future.
    5. Predict. Finally, data is ready, context is known. Now, our Data Scientists can start their work in knowledge, put the time into what the organization wants to know, use the tools where they have expertise, Machine Learning, AI, Deep Learning, and algorithms that put together data and context in order to have a better understanding of what to expect from the upcoming scenarios.

    At Vybrant, we establish a dedicated team of Data Science & Data Engineer experts to research and build custom Machine Learning solutions that will scale up our clients. Our team of engineers analyzes data, takes fast and reliable insights from it, and builds models to identify patterns that provide accurate and faster solutions for our clients.

    With our in-depth experience in problem solving and business transformation, we are the perfect partner and Machine Learning development company to help businesses gain value from their raw datasets.

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Desenvolvido por DMX Design