Data-Science Development Platform


Data science is becoming an every day a must essential discipline in most organizations. Data is the new oil and data science is the way to mine this data and refine it to useful data in your organization specific tasks. Everyday new problems arises and organizations are using data-science to get answers from their data sets.

Orchestrating the complete workflow from extraction > preparation > transformation > modeling > app development > app deployment to users is a very demanding process to data-scientists, it takes a lot of computing and storage management and integrate multiple machine learnings models, development environments and no code app development makes the process of creating a working AI Application work for months.


DataKubes is a complete Data Science Orchestrating and Data App Development, design to simplify the process of adopting Data-science in any type of organization. Taking the management and integration process from months to days.

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DataKubes Orchestrator

Full Set of DataTools for data-scientists

The DataKubes Orchestrator bring together a set of data tools to the hands of any type of data-scientist. The following tools are available out of the box:

  • DataPipes for extraction.
  • Computing Objects for Python, PHP, AutoML, Tensor-flow, Keras and more containers.
  • Storage Management using SingleStore Cluster.
  • DataObjects Management.
  • Data Profiling for ML Feature selection and data analytics.
  • Custom Extraction and Preparation using Python and PHP containers.
  • External tools integration like MapBox and Clearbit for enriching data.
  • DataKubes for creating Visualization Cubes for multidimensional data visualization.
  • Api Tokens for sharing data stored in the storage repositories using DataKubes API.
  • Data Forms for creating public or internal web forms for enriching data directly to data objects in repositories.
  • Alert rules for creating business logics for detecting data matches and pushing notifications to users in web, email and mobile devices.

DataKubes simplifies the overall AI/ML Adoption to your organization, using a single point of Orchestration of Storage and Computing Power, all focused to enable not just AI/ML Inventory Optimization solutions but the platform to create new AI/ML Applications to responde to the most demanding questions and unsolved problems

NoCode App Development

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Example of DataApp for Customer Churn

DataKubes brings the DataApp Studio a complete no code app development environment design to help data-scientist to build AI/ML apps connected to their orchestrator projects. This makes the process of sharing to public or internal users a complete User Experience based on the data available in the DataKubes

DataApp Studio Features

  • No Code Development Environment.
  • Screens creation and relationship.
  • User management based on DataKubes users or custom user table.
  • Machine Learning screen integration to DataKubes Workshop.
  • More than 10 types of screens to use.
  • Easy to learn and use UX interface.
  • Direct integration to data repositories.
  • Growing set of tools added every month to enrich and empower different types of scenarios.

DataApp Studio Screens types

  • Dashboard drag and drop designer.
  • Configuration Screen. Table Edit Screen with custom form for adding and updating data.
  • Menu Hidden Screen Group for creating better UX for users.
  • DataKubes Workshop project runner, for running AI/ML models on demand.
  • Search to Dashboard screen for creating related data overview.
  • Dashboard Creating for easy access to users from their home screens.
  • Direct integration to data repositories.

The process of adopting machine learning in your organization is a complex process made simple by DataKubes, from infrastructure on premise or cloud, to the deployment of DataApps, Custom Server-less App/Api. A complete simple AI/ML Orchestrator platform at your service.

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Use Cases

  • Bioscience and Biotechnology.
  • Oil and Gas.
  • Healthcare.
  • Insurance.
  • Energy. Education.
  • Banking and Finance.
  • Marketing.
  • Public Sector.
  • Retail.
  • Distribution and Transportation.