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Showing posts from October, 2017

Need for Speed: How We Optimized Performance in the Joget Workflow v6 Platform

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As an open source low-code / no-code application platform , Joget Workflow allows both non-coders and coders alike to visually build apps rapidly. Beneath this simplicity though, there is a lot going on and performance has always been a priority. The focus is to provide a fast runtime for apps, and we diligently try to ensure that there is as little overhead as possible at the platform level. The Joget team has been hard at work on Joget Workflow v6 , currently in public beta. We have recently been looking into ways to streamline and optimize performance of the platform even more. This technical article details how this was done for the latest beta release, and could provide helpful tips for your own projects or products. The article gets quite technical and is targeted at developers interested in the inner workings of the platform. Let’s take a look under the hood. Server-Side Code Profiling The Joget platform is built on Java, so numerous code profiling tools are available j
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No-Code, Low-Code and Pro-Code: Why Flexibility is Essential for Digital Transformation

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Introducing Business Reporting and API Management Addons for Joget DX The COVID-19 coronavirus pandemic will be viewed in history as a significant point in human history. In the post-pandemic world, digital transformation can no longer be delayed and organizations need to adapt quickly, or perish, as the old ways of working no longer apply in the new normal. Based on Forrester’s Q1 2020 Digital Process Automation Survey , over 70% Of organizations still have paper-based process dependencies, as shown in the figure below. With a modern open source no-code/low-code platform like Joget DX , organizations can rapidly build, deploy and adapt applications to cater to ever changing needs. In this article, we will talk about the need for flexibility in application platforms to meet digitalization needs, and how the extensibility of Joget DX enabled the introduction of new add-ons for business reporting and API management . No-Code, Low-Code and Pro-Code: Flexibility and Extensibility There mi
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How to Solve Your Enterprise App Performance Problems

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Enterprise applications are inherently complex, and performance problems are unfortunately a common phenomenon. This article describes some of the most common performance issues, and provides insights to help you identify problems and eventually optimize the performance of your apps. The content here is tailored for the Joget platform, but the information provided can be applied generally for any enterprise environment. Joget is an open source no-code/low-code application platform that empowers business users, non-coders or coders with a single platform to easily build, deliver, monitor and maintain enterprise applications. Getting apps built and deployed quickly is important, but having them perform well is essential. At the platform level, Joget has been optimized and streamlined as outlined in the article Need for Speed: How We Optimized Performance in the Joget Workflow v6 Platform . The Joget platform already takes care of a lot of things under the hood for running your apps. H
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Transforming Customer Onboarding: How Allied Benefit Systems Achieved Reporting Accuracy and Streamlined Business Processes with No-code/Low-code.

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To optimize business operations and ensure accurate reporting, Allied Benefit Systems empowered business users and delivered a Customer Onboarding Platform built on no-code/low-code within three months. Effective onboarding processes play a crucial role in creating a positive impression on new customers. Yet, many businesses still need to rely on manual methods that can be time-consuming, error-prone, and inefficient. Allied Benefit Systems (Allied) , a US-based healthcare solutions company that prioritizes people, understands the importance of streamlined onboarding. As the largest independent third-party administrator in the US, Allied designs tailored self-insurance benefits solutions that integrate innovative medical management and cost-control strategies.   The company collaborates with clients and benefits consultants to institute plans that support the best options for employees and their families. However, Allied's existing onboarding process was managed through spreadsheet
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DISINI™ Vehicle Inspection & Insurance App

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The DISINI™ Vehicle Inspection & Insurance App is an application that can be used standalone or in a composable application environment on the Joget DX low-code platform. Enterprises will be able to use the application to manage their fleet of vehicles, track insurance policies expiry and conduct regular vehicle inspections. Summary of the App features are: Track your vehicles' insurance policies and set email reminders of the renewals. Assign inspectors to conduct scheduled vehicle inspections. Supervisors will be able to set reminder notifications for the inspectors of upcoming vehicle inspections. Inspectors will be able to check their calendars for scheduled inspections that have been assigned to them. Create and manage inspection checklists templates for the many vehicle types. Inspectors will be able to update and check their Dashboard for inspection tasks. Supervisors will be able to keep track of all assigned inspection tasks and follow up accordingly. The following ar
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A Quick Introduction to Artificial Intelligence, Machine Learning, Deep Learning and TensorFlow

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What used to be just a pipe dream in the realms of science fiction, artificial intelligence (AI) is now mainstream technology in our everyday lives with applications in image and voice recognition, language translations, chatbots, and predictive data analysis. In this article, we’ll introduce AI along with its related terms machine learning and deep learning. By the end of the article you should understand these terms, how things generally work and be more familiar with terms like Inception and YOLO (and no, we’re not talking about the Leonardo DiCaprio movie or some internet meme). Artificial intelligence (AI) is the simulation of human intelligence by computers. Machine learning is a branch of AI where algorithms are used to learn from data to make future decisions or predictions. Deep learning is a specific subset of machine learning using artificial neural networks (ANN) which are layered structures inspired by the human brain. The following diagram shows more clearly
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