Future of RPA: In-depth Guide to RPA Innovation in 2019

RPA tools are the most successful generalist automation tools for the modern enterprise but implementing RPA is not without pitfalls as we outlined before. Leading solution providers are working to simplify/facilitate the 2 most expensive portions of RPA deployment: 1- Design & development and 2- maintenance.

1. Making RPA programming easier: No code RPA

Simplifying RPA programming will help democratize RPA and expand its use. Currently, most automation through RPA is achieved through programming which is one of the most major costs of RPA implementation. It’s also a limiting factor as RPA developers are required for RPA development. Unless you know the latest no code RPA solutions, you could get stuck with a long programming period and heavy reliance on 3rd parties. Read more

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AI solutions can transform businesses, boosting sales by up to 35%, reducing wage costs by 60%

In each AI use case, there are numerous vendors. Even after hours of research, you can easily miss major solution providers or smaller but more innovative solution providers.

Fill out our form, so most suitable vendors for your business in your area of interest can reach you

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RPA whitepaper [2019 update]

A responsive, lean organization that delivers results is the goal of every executive. Robotic Process Automation (RPA) provides the flexible yet powerful automation tool to achieve that.

In this comprehensive guide, we explain in detail how RPA can be applied in your business and provide answers to any RPA related questions such as types of RPA, its application areas and its benefits

Table of contents

Executive Summary

Introduction

Manual processes are holding your organization back

Industries ripe for automation with RPA Read more

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Security Analytics in Age of AI: In-depth Guide [2019 update]

Every day 2.5 quintillion bytes of data are produced. Some of it is important (and private), like the most essential of financial and medical records. Some of it, like the cleaning path taken by an IoT vacuum is largely useless (or is it?). And all of it can become vulnerable without the right security effort.

Subsequently, there is a growing need for us to find new and better ways to protect our most sensitive data from a host of digital threats rise. Cybersecurity analytics can ultimately help to lay the foundation for large scale data protection.  Some questions that this post sets out to answer include:

What is cybersecurity analytics?

What are the benefits of cybersecurity analytics?

What are some common cybersecurity use cases?

How do AI and cybersecurity analytics go together?

What are some best practices for cybersecurity analytics?

What are some pitfalls/challenges in cybersecurity analytics?

What are tools to aid in effective cybersecurity analytics?

How can I start to establish a cybersecurity analytics program in my organization?

What is Cybersecurity Analytics?

Every day millions of cyber attacks are successfully executed around the world. Though it may be impossible to 100% prevent them all, we can certainly learn from them to help develop better ways to stay protected. Cybersecurity analytics studies the digital trail left behind by cyber criminals to help better understand weaknesses and how to prevent similar losses in the future.

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Workforce Analytics: Guide for Businesses [2019 update]

Employees are one of the biggest investments that an organization can make, so it’s not surprising that the field of workforce analytics has emerged to help support it. And with the amount of data that is being generated and recorded about not just employees, but the organization as a whole, the time is ripe for analysis. This is becoming even more true as our working population expands to include alternative forms of employees in chatbots and similar. 

In this post we will introduce workforce analytics by answering the following questions: Read more

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