Prateek Khurana
Prateek is Business Head, Grid Infocom

Comments (2)

  1. My question to RPA vendors is how robust are your scripting technologies? Software testing of enterprise applications has used RPA techniques. For robustness RPA for QA has always required specialist QA engineers to develop and build tests for the tests. Early on even pixels instantiated on different Windows boxes due to different graphic card and resolutions could throw long running RPA test results into the bin. Later resource IDs behind the UI were used, more so after Microsoft provided Visual Test with Visual Studio/MSDN. Screen scraping came with web browsers, used by data scientists” to harvest content without API”s. Screen scraping is often fragile needing developer attention to fix scripts. Is RPA another technology for giant consulting firms with developers working alongside business people? Is RPA”s main value the ability to interface cloud-based AI? Is RPA another rat race like EDI?

  2. Hello, thanks for your interesting query.

    Before I respond to the questions, I’ll like to share a brief about how RPA differs from old automation methods. Firstly, RPA is system agnostic, which is one of the key differences from the old automation processes. RPA enables several tangible and measurable values such as low investment cost, non-disruptive system integration, and rapid implementation.

    There were generally two types of automation:
    1. Screen scraping/capture
    2. Product specific workflows

    The modern-day RPA platforms are enterprise scalable. Processes are built by showing the robots what to do, step-by-step, rather than coding or scripting them, in exactly the same way as a human would use the end-user systems.

    The tools also ‘recognize’ the fields or pop-up screens they are working with rather than relying on a location on the screen. The software robots used in RPA ‘read’ the applications using APIs or the operating system itself. It is part of the training of the robot where it is shown how to read the various screens it needs to work with.

    As a result, RPA tools today are business tools for non-technical users. In the past, this was not the case, with many of the older automation tools being bespoke to a specific product, they could not easily be deployed on a large scale, and required specialist technical resources to setup and maintain them.

    To sum it up:

    · RPA tools today are business tools for non-technical users and flexible enough to work in different models

    · RPA is system agnostic, making it interesting to work with any kind of technology and will easily work on cloud-based AI too

    · RPA is far more advanced than EDI. In fact, RPA is the first step to AI. Cognitive learning and AI are a part of the immediate roadmap for all platforms

    I hope this has answered your queries. If there’s anything else, I’d be happy to connect with you over email as well. You can write to me at

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