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KAISPE has been providing solutions and services to customers using Microsoft Dynamics, Azure, Power platform, Oracle NetSuite, mobile and web app development.

    • US OFFICE
    • +1 315 791 4472
    • KAISPE LLC
      590 Madison Avenue 21st Floor Manhattan, NY 10022 USA.

 

  • PAKISTAN OFFICE
  • +92 213 432 6085
  • M/S KAISPE
    Suite#213 Sumya Business Avenue MACHS Karachi, Pakistan.

Month: April 28, 2020

  • April 28, 2020
  • jdkaispe

Developing Custom Connector in MS Power Automate using Azure ML Services

Recently we had a chance to work on developing a custom connector in Microsoft Power Automate. We had to consume Microsoft Azure Machine Learning Services model using REST API and […]

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  • April 20, 2020
  • jdkaispe

KAISPE IoT Web Portal is now Integrated with Microsoft Dynamics 365 (CE)

NEW YORK, April 20, 2020 – KAISPE is pleased to inform that our IoT Web Portal is now integrated with Microsoft Dynamics 365 Customer Engagement using Microsoft Azure LogicApps. This […]

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  • April 14, 2020
  • jdkaispe

Robotic Process Automation – Automate Time Consuming Manual Processes

Automation has always been a key to businesses to achieve higher productivity and lower the operating cost by avoiding repetitive tasks. With recent situation where social distancing is playing a […]

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  • April 13, 2020
  • jdkaispe

MS Power Automate: Difference between Automated vs Instant vs Scheduled Flows

Organizations are committed to optimizing the use of resources to deliver the required business results. The goal is to enable smarter processes throughout the enterprise to enhance collaboration, reduce delivery […]

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  • April 11, 2020
  • jdkaispe

KAISPE Employee Churn Dashboard

Employee Churn prediction has always been a challenge for organizations. Powered by Microsoft Azure Machine Learning Services, our Power BI dashboard gives you useful insights into employee churn prediction. You […]

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  • April 8, 2020
  • jdkaispe

Consuming Azure ML experiment web service using Visual Studio

As I was working on Student Churn Prediction model using Azure  Machine Learning (ML Experiment Web Service). My goal was to consume a Web service using a CSV as input […]

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