Automation | Read the latest blogs, news and views from Infomentum.

Occasionally, I’ll come across a project where I encounter an interesting challenge or two. In one of these instances, I was working on an automation project for a customer who wanted to ingest all of their quotes from different suppliers into their Salesforce application. The quote documents were highly unstructured PDFs and Excel files, requiring the design of a bot which would extract data from these files and ensure that mandatory information was loaded into the Salesforce application using OCR technology.

Introduction

When I embarked on my latest project involving MuleSoft's Robotic Process Automation (RPA), little did I know it would be one of the most challenging yet rewarding experiences of my professional journey. As someone who enjoys solving complex puzzles, I was eager to dive into the intricacies of RPA; however, I soon realised this project would test my skills and patience in ways I hadn't anticipated. Balancing work and personal life became crucial, as late nights and early mornings became routine. However, with a steadfast commitment to overcoming each obstacle, the end result was immensely satisfying.

Introduction

Not long ago, our team came across a surprising new issue when running bots in live VMs. To provide some context, by default each VM deployed for automation has 2 user accounts that can work concurrently. In this case, we deployed 2 parallel instances of the bot to optimise the throughput. 

In the ever-evolving landscape of automation, the integration of bots across multiple systems has become a necessity for efficiency and productivity. However, as this technology progresses, a critical challenge has emerged as well. It's become increasingly difficult to balance the benefits of formatted and structured information for human use while also working towards the reduction of semantic resolution.

Introduction

Robotic Process Automation (RPA) progresses through distinct phases in its project life cycle. When it enters the production deployment phase, the bots are deployed onto dedicated machines to carry out end-to-end automation. It is at this stage that scheduling comes into the picture, guiding bots on when to run and on which machine.

The scheduling step is relevant for bots that run in an unattended/automatic way at specific intervals (often many times a day!). However, it does not apply to bots that are attended or triggered by human or system actions.

Plunging head-first into the world of Robotic Process Automation (RPA) would make anyone feel uneasy. With a scientific and mathematical background and experience with Python, I was overwhelmed by the unfamiliar terrain of new technology in the corporate tech world.

But, interested in the world of RPA and how it could potentially transform the way we work, I adjusted my mindset to being ok with feeling uncomfortable.

In the first part of the blog, I described the basics of Anypoint Code Builder. Today, I will guide you through the design phase of the ‘Hello World’ project.

MuleSoft Composer is a no-code integration platform that enables users to integrate data and apps easily. The process starts by building flows using various pre-built connectors, including Salesforce, Workday, Slack, MuleSoft RPA, and others.

In this blog, I will describe the API-based integration between Breathe HR and Tempo with MuleSoft Composer. Breathe HR is a cloud-based HR software, and Tempo is a time-planning and logging app integrated with our Jira.

Today we'll complete the automation of our internal celebration process. In the previous blog, we explained how to invoke a bot from the MuleSoft Composer to discover the next upcoming birthday or work anniversary. It is time to create a robot responsible for ordering cupcakes from Lola's website to mark the special occasion.