Rapid Application Development System™ (RADS™)

In MLP (Machine Learning Processor), data cleaning, parsing, flow modeling and processing, machine learning, and reporting are all programmed graphically, without writing software code. This system is called Rapid Application Development System™ (RADS ™).

  • RADS:
  • Enables easy drag-and-drop graphical programming that the data solutions engineer can rapidly create
  • Minimizes or eliminates coding because the components used in the models are pre-coded and fully tested.
  • Reduces the involvement of software engineers for writing production-ready data integration and analysis code.
  • Reduces bugs and testing time.
  • Enables faster solution development and deployment.


Develop input integration and parsers


Develop data models


Develop visualization and output integration

RADS Innovation

Traditionally, software engineers put together open source software with the help of custom software code.

Then they collaborate with data scientists to create solutions for operational data analysis.

Disadvantages of traditional way of Stream Data Analytics
  • Takes too long to deliver solution
  • More parties involved. Cannot get exactly what is envisioned
  • Costs a lot more
  • Hard to maintain and improve
Advantages of MLP RADS™
  • Order of magnitude Faster time-to-delivery
  • No need for data scientists who are also expert programmers
  • Fewer bugs and problems
  • Get what data scientist envisioned
  • Easy to maintain and improve
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