Digital Workers Are a Necessity in Our Post-Pandemic World

Digital Workers

Modern growth depends on automation. Any routine task that can be automated gives an enterprise an edge over the competition in the beginning and then becomes a necessity for survival.

Excel macros were once a boon to any data-driven enterprise. They allow data analysts to automate processes that involved a lot of error-prone copying, pasting, and time. The problem with Excel macros is that they are limited to automating Excel and other Microsoft products.

A modern enterprise will have a suite of software that will benefit from automation, software that must work together to get the job done. Robotic process automation, or RPA, can automate routine processes at the user interface level regardless of the underlying software stack and takes automation to the next level, automation of any software an enterprise uses.

But automation has evolved even further than RPA. Let’s look at what digital workers are and how they can change your business.

What Are Digital Workers?

Using robotic process automation, you can create bots. Bots automate very specific processes and usually have a narrow range of functionality. Note that digital workers are not bots. Digital workers can handle a broad range of tasks that would roughly correlate to a human job description. You can think of them as a fleet of bots that you deploy for a complete task.

Use cases for a digital worker include:

  • Data entry
  • Updating CRMs, ERPs, and billing
  • Employee onboarding
  • Client onboarding
  • Claims processing
  • Account reconciliation
  • Invoice processing

Digital workers are designed for specific job roles, so you don’t have to track down all the repetitive processes you use and map RPA bots to each task. Instead, you just download a digital worker, configure it, and put it to work.

The Benefits of a Post-Pandemic Digital Workforce

The pandemic brought many businesses to a halt. For others, it took a while for employees to adjust to working remotely. Business models changed forever, and digital workers have become an invaluable asset for organizations to thrive in this new world and adjust to changes quickly.

Here are some benefits of using digital workers:

Accurate Data

Many of the jobs you can replace with a digital worker involve data. Human data entry has always been susceptible to errors. It’s just the nature of being human. Digital workers take error out of the equation by cross-checking information and flagging any issues for a human to review.

Faster Processing

A digital worker can work faster than a human can type. Jobs that once had to be calculated in working hours can now run unattended in a fraction of the time. Digital workers also don’t need breaks and can work all day long.

Increased Productivity

Automating tedious, manual tasks like data entry will free up employees’ time to focus on more important tasks. Employees will be motivated to work on more interesting tasks when they aren’t interrupted by menial work. Digital workers can work 24/7 and don’t take sick days.

Lower Costs

All the other benefits of digital workers add up to a lot of savings. Without human error, tasks won’t have to be done twice. Because digital workers can process tasks faster, your business can get more done each day. And employees can work on important tasks while digital workers automatically and economically take care of all the menial tasks.


The pandemic changed the way business is done. Businesses are undergoing digital transformation to keep up with the changes in the pandemic’s aftermath. Digital workers are an important part of this transformation. They can automate processes once done by employees with more accuracy, faster processing, and lower costs while freeing employees to do more important work.

Our team at Idexcel offers Automation and AI services for your business. With over 21 years of experience in every aspect of intelligence, automation, and AI, we can help you digitally transform your company. Get in touch with our team to schedule your free assessment.

Why Are Cloud-First AI Solutions Important?

Nearly everywhere you look in today’s global marketplace, you’ll spot an ever-increasing use of artificial intelligence (AI) solutions combined with cloud computing technologies. You might even personally use AI in cloud solutions in the form of digital assistants, such as Apple’s Siri, Amazon’s Alexa, and Google Home. But how far down the AI solutions rabbit hole are you ready to take your business?

If you are still on the fence about adopting AI in the cloud for your enterprise, you might benefit from exploring why cloud-first AI solutions are vital to your business’s growth now and in the future.

Keep reading to learn the most crucial benefits of investing in a cloud AI platform.

Transformative IT Infrastructure That Spurs Growth and Competition

Today’s top AI cloud platforms, like AWS, are reimagining and transforming traditional IT infrastructure to help you keep up with the competition within your industry. It comes down to your potentially falling behind the competition if you don’t adopt AI in the cloud, making it a little like high-tech peer pressure thanks to the increasing demand for AI-optimized cloud application infrastructure. Basically, everyone is doing it, so it’s best to stay ahead of the curve to minimize the need for a panicked adoption later.

The top vendors make it easy for you by introducing specialized IT platforms that feature pre-designed storage and computing resources combinations to streamline the learning curve for you and your team.

cloud and AI

Enhanced Data Access and Data Analysis

AI and data go hand-in-hand, and to a degree, data feeds AI, allowing it to learn and become smarter. Essentially, your computing system learns more without explicit or manual programming. Add to that benefit the cloud’s nearly unlimited data storage capacity, removing delays and other obstacles, and your AI is free to gather, analyze, and interpret data. With massive tomes of data and unlimited resources to access it, your AI can make predictions regarding matters like risks and troubleshoot those issues before they boil to the surface as bona fide problems. Further, training machine learning models is much easier in the cloud. With the right solution, machine learning options don’t require in-depth and intensive AI knowledge, extensive familiarity with machine learning theory, or a group of data scientists.

Reduced Costs

Think about all the time and resources your business has invested in infrastructure upgrades and adding on-site storage, then imagine a business model that removes those concerns. The top cloud AI platforms can do that for your organization and much more. With a cloud AI solution, you can purchase only the amount of storage you need for the data you currently possess and what you anticipate ahead, knowing you can scale to your enterprise’s needs. It also frees your IT team to manage on-site matters, such as purchasing, installing, updating, and maintaining employees’ hardware devices.

AI cloud platforms also reduce or eliminate the need for your executive and IT teams to perform continuous tech research in a field where everyone struggles to keep up with the latest trends and innovations. Your AI cloud service provider stays up-to-date on these concerns as a matter of course, therefore able to pass the benefits of their work along to your business, further allowing your team to attend to core business functions.

Are You Ready to Adopt Cloud-First Solutions for Your Enterprise?

Adopting a cloud-first solution puts you on track for keeping up with the competition at a minimum, and along with your own strategies, it will help you move far ahead.

Our team at Idexcel can help you determine and launch the best strategy for seamless AI cloud adoption. For more than 21 years, we have delivered professional services and technology solutions with specializations in cloud services, cloud-native services, data platforms, and intelligence to satisfied, loyal clients. Get in touch with our team to schedule your free assessment.

Business Impacts of Data Extraction Solutions

The Current Digital Automation Climate

Digital disruption in the form of automation has caused a massive change across the globe that has affected all industries in various ways. AI-powered automation solutions reduce the time spent on repetitive tasks and offer massive benefits to stakeholders. Currently, the manual extraction of data from hundreds of documents, creation of spreadsheets for record-keeping from that data, and analysis to confirm a business outcome happens on a massive scale every day. It can be so time-consuming and frustrating, especially with the possibility of errors and duplications. If left undetected and uncorrected, these discrepancies can magnify into much larger issues downstream.

If these manual tasks could be accomplished in a fraction of this time by a digital resource, imagine how much time can be freed up for the most critical aspect to business success: human intelligence. More and more organizations are shifting from manual processes to solutions that leverage AI-powered data extraction tools that become more intelligent over time using ML (Machine Learning). Business executives are turning to AI to cut out repetitive tasks such as paperwork (82%), scheduling (79%), and timesheets (78%) (Source: PWC). By harnessing the power automation and ML, Idexcel data extraction solutions can identify, extract, and analyze data from all types of sources at phenomenal speed with tremendous accuracy.

How does AI fit in with Data Extraction?

It is extremely important for companies to have a strong, data-driven strategy in place as the foundation to build AI solutions on. Statistics reveal that businesses engaging in data-driven decision-making experience almost 6% growth in productivity. This reinforces the importance of understanding how smart data extraction can improve business operations. The challenge is that the actual process of mining and analyzing the essential data has become extremely arduous due to unstructured data. In fact, IDC projects that 80% of the total data will be unstructured by 2025, which will pose a challenge for organizations that are not properly prepared with a data strategy in place.


Data extraction using AI works in a self-sustaining way by training itself on billions of relevant data pieces, understanding formats, and evolving to optimize performance over time. Using NLP (Natural Language Processing), Deep Learning, OCR (Optical Character Recognition), and our customized proprietary framework, this solution delivers ready to use data for analysis to drive valuable business-critical insights.

Impact of AI-Powered Data Extraction in Banking and Financial Services

Banking and Financial services operations include processing millions of documents that are filled with both unstructured and structured data every day. These organizations must hire a huge and expensive workforce to complete the necessary data extraction, data processing, retrieval, and storage procedures. ML-powered solutions reduce this need to drive greater efficiency and productivity across multiple operational areas in the financial services and banking sector:

  • Speeding up the extraction of relevant information from mortgage documentation, contracts, financial reports, and other sources.
  • Accounting operations including AP & AR Statement Data Extraction
  • Payroll processing of timesheet reconciliation for Invoice creation and submission
  • Financial reporting to ensure compliance with regulations on contracts, applications, and other requisite documents.

The possibilities for applying this solution are endless. Supply chain management, retail, ‘marketing, insurance, and real estate are also key industries in which an Invisible Automation solution can be used to elevate operations.

Key Advantages of Data Extraction Solution

  1. Earn More Customer Loyalty: Loyal customers are the most significant assets for any organization. Taking considerate, data-driven steps to make the experience better for them fosters a positive and long-lasting bond based on trust.
  2. Accelerates Information Processing: Automation of manual and repetitive tasks like extracting data points from invoices and forms significantly accelerates the information processing procedures, resulting in faster information to be analyzed for stakeholders to make critical business decisions.
  3. Saves Significant Time: Time is one the most indispensable resources for any organization. In a world that is constantly bombarded with billions of data at a rapid rate, relying on the speed and accuracy of manual labor introduces operational vulnerability. Automation gives back time and energy to team members to focus on creative thinking, innovation, and building meaningful services.
  4. Cost optimization: With consumer demands, habits, and buying behavior shifting while the market competition increases, it has become exceedingly difficult to reduce costs. Manual extraction of data and unnecessary staffing will pose an even bigger challenge. Try a data extraction solution and you can get the same job done accurately, economically, and promptly.
  5. High Accuracy: Data extraction and data entry are highly error-prone tasks. Even if done with much diligence and precision, small mistakes are bound to happen. These small mistakes in thousands of documents might amplify into issues and future regret for the company. Also, you will end up jeopardizing the much-needed time and money to no avail. But by just using a data extraction solution, you can be assured of zero errors and prompt execution.
  6. Focus on Primary Objectives: Optimal productivity of employees is of paramount importance for any corporation’s prosperity. Forcing employees to perform monotonous and exhausting tasks, which provide no real value to the company, lowers their productivity and enthusiasm drastically. This also reduces job satisfaction and will slowly but surely, negatively impact the company. Incorporating automation will remove this unnecessary burden from the employees’ shoulders while enhancing productivity. This will spare the much-needed time for employees to focus on more meaningful tasks. This will transform into a win-win situation for the employees and employers.
  7. Improve Data Accessibility: An intelligent and automated data extraction tool enhances the visibility of the incoming data, its storage, and retrieval, making it readily accessible whenever necessary. A survey by Forrester suggests a 10% increase in data accessibility can augment the net revenue by a whopping $65 million for a typical Fortune 1000 company.

In a time where consumers are changing the way they interact with companies’ digital infrastructures, it’s imperative to consistently transform your organization to equip it with the latest technology. Processes will continue to become automated, more intelligent, and enable human resources to focus on elevating product/service delivery and driving business success. By leveraging ML-powered AI with automation tactics, data extraction solutions can skyrocket productivity and churn explosive revenue at a fraction of the original time and costs incurred. Ready to get started building an elegant operational infrastructure to optimize resource allocation, reduce overhead costs, and establish a competitive edge? Get connected with an Idexcel expert today.


AWS re:Invent Recap: Werner Vogels Keynote

Major Service Announcements:

  1. NEW: AWS CloudShell is a browser-based, pre-authenticated shell that can be launched directly from the AWS Management Console to run AWS CLI commands against AWS services using a preferred shell of Bash, PowerShell, or Z shell. This can all be completed without downloading or installing command line tools. AWS CloudShell is generally available in us-east-1 (N. Virginia), us-east-2 (Ohio), us-west-2 (Oregon), ap-northeast-1 (Tokyo), and eu-west-1 (Ireland) at launch.
  2. PREVIEW: Chaos Engineering with AWS Fault Injection Simulator is a fully managed chaos engineering service that makes it easier for teams to discover an application’s weaknesses at scale in order to improve performance, observability, and resiliency. Developers can now specify conditions to create real-world scenarios that allow hidden issues to be revealed, monitoring potential unforeseen issues, and identify bottlenecks that might affect performance that are usually very tough to find.
  3. PREVIEW: Amazon Managed Service for Prometheus (AMP) enables developers to ingest, store, and query millions of time series metrics, increasing scaling capabilities. This Prometheus-compatible monitoring service makes it easier to keep track of containerized applications at a larger scale.
  4. PREVIEW: Amazon Managed Service for Grafana (AMG) is a secure data visualization service that allows users to query, correlate, and visualize various operational metrics, logs, and traces across multiple data sources to increase observability.

Why it Matters:

There were some major themes we noticed throughout the presentation that really resonated on how to help meet customer needs, wherever they are in their digital transformation journeys:

1. Architecture Sustainability: One of the biggest focuses for many organizations is analyzing the sustainability of their architectures and the impact it has on operations. Once COVID-19 forced companies to adapt how they work, looking at technical architecture strategies is no longer about working from home. It’s about working anywhere, with the right tools available to complete the work necessary that drives business success. AWS tools and new services launched enable development teams to build better solutions, but also to help our clients bring more sophisticated solutions to market faster.

2. Dependability: Another critical theme discussed was the need for solutions to be dependable and not bound by latency. Availability, reliability, safety, security are all properties of dependability that must be considered when building solutions. This is why we’re excited about the new fault removal, forecasting, and Chaos Engineering tool announced, AWS Fault Injection Simulator. This enables weaknesses to be identified quickly to be fixed, addressing the common challenge IT teams have adequately stress-testing cloud applications and. With the integration of the AWS Fault Injection Simulator, we will be able to stress-test applications at a much faster clip to ensure greater dependability in solutions we deliver to our customers.

3. Observability: Many organizations that have various systems generating and storing terabytes of data would benefit from an end-to-end observability that displays optimized analytics and valuable insights to IT and leadership teams. The sheer amount of data could be massive and near impossible to integrate into one core dashboard without the right tools and approach. That is why we are excited about the logging, monitoring, and tracing capabilities that will be available in the latest of two core service previews announced:

Amazon Managed Service for Prometheus (AMP) is a tool that automatically scales the intake, storage, and analytics queries when workloads sizes change and are integrated with AWS security services to. The service works with Amazon EKS, Amazon ECS, and AWS Distro for OpenTelemetry, enabling fast and secure access to required data sources.

Amazon Managed Service for Grafana (AMG) is a fully managed service that can be leveraged to create on-demand, scalable, and secure Grafana workspaces that create visualization elements and perform data analyzation from multiple sources.

4. Customer-Centricity: Every organization has a unique digital transformation journey with very specific needs that requires a tailored approach to build a solution that has an impact. Werner reiterated his message of building with customer needs in mind on Twitter by saying, “Think about what you can do to meet your customers where they are.” He reminded us to be conscious of important issues up front while designing products – services, interfaces, and user experience features that could help address their concerns during an uncertain time for many. It is critical that the services we build to address operational problems should consider the experiences we’re creating for people.

Are you ready to construct your Digital Transformation Roadmap or need to know a little more about how we can help? Get connected with an Idexcel expert to schedule your assessment today!

AWS re:Invent Recap: Infrastructure Keynote

Here are the key discussion topics from the AWS re:Invent 2020 Infrastructure Keynote from Peter DeSantis – Senior VP of Global Infrastructure and Customer Support, with a focus on efforts to improve resiliency, availability, and sustainability for its customers:

  1. AWS Nitro System: Enables faster innovation and enhanced security. Nitro version hypervisor chips is the most recent generation of instances built on the AWS Nitro System is the C6gn EC2 instances
  2. AWS Inferentia: AWS Inferentia is Amazon’s first machine learning chip designed to accelerate deep learning workloads and provide high-performance inference in the cloud.
  3. AWS Graviton2: Graviton 2 processors are the most power-efficient processors AWS provides, achieving 2-3.5 times better performance per watt than any other processor in AWS’s portfolio and is suitable for a variety of workloads.
  4. AWS Commitment to Renewable Energy: A customer moving from an enterprise data center to an AWS data center can reduce their carbon footprint. UPS and data center power and the changes there save 35% lost energy in power conversion and 6,500 megawatts of renewable energy utilized across the world.
  5. New Infrastructure Design: AWS is implementing a new infrastructure design that replaces single, large UPSs from their infrastructure with custom-built power supplies and small battery packs and power supplies, placing them directly into every data center. These micro UPSs are intended to reduce complexity and maintenance and improve availability.
  6. Regions and Availability Zones: AWS continues to invest in more regions and Availability Zones (AZs) around the globe. Italy and South Africa launched earlier in 2020, and Indonesia, Japan, Spain, India, Switzerland, and Melbourne are in the works. Explore AWS’ interactive global infrastructure site here.

If you’re looking to explore these services further and need some guidance, let us know and we’ll connect you to an Idexcel expert!

AWS re:Invent Recap: Amazon SageMaker Edge Manager

Recap Amazon SageMaker Edge Manager

What happened?

Amazon SageMaker Edge Manager was announced during the re:Invent Machine Learning Keynote. This new feature gives developers model management tools for to optimize, secure, monitor, and maintain machine learning models on fleets of edge devices such as smart cameras, robots, personal computers, and mobile devices.

Why is it important?

  • Device Compatibility: It enables developers to train ML models once in the cloud and across fleets of devices at the edge.
  • Optimize ML Models: Amazon SageMaker Edge Manager provides a software agent that comes with an ML model optimized with SageMaker Neo automatically. This eliminates the need to have Neo runtime installed on devices to leverage model optimizations.
  • Reduce Downtime and Service Disruption Costs: SageMaker Edge Manager manages models separately from the rest of the application so update the model and the application independently reducing downtime and service disruptions.

Why are we excited?

The new SageMaker Edge Manager helps data scientists remotely optimize, monitor, and improve the ML models on edge devices across the world, saving developer time and customer costs. It reduces the time and effort required to get models to production, while continuously monitoring and improving model quality.


It’s available today in the US East (N. Virginia), US West (Oregon), US East (Ohio), Europe (Ireland), Europe (Frankfurt), and Asia Pacific (Tokyo) regions.

If you’re looking to explore these services further and need some guidance, let us know and we’ll connect you to an Idexcel expert!

AWS re:Invent Recap: Amazon SageMaker Debugger

Recap Amazon SageMaker Debugger

What happened?

Amazon SageMaker Debugger, a tool that monitors machine learning training performance to help developers train models faster, was announced during the re:Invent 2020 Machine Learning keynote. This tracks the system resource utilization and creates alerts for problems during training. With these new capabilities, automatic recommendations for resource allocation for training jobs, resulting in an optimized training process that reduces time and costs.

Why is it important?

  • Monitor Automatically: Amazon SageMaker Debugger enables developers to train their models faster through automatic monitoring of system resource utilization and alerts for training bottlenecks or bugs.
  • ID & Resolve Issues Faster: Amazon SageMaker Debugger provides quick issue resolution and bug fix actions with automatic alerts and resource allocation recommendations.
  • Customizability: With SageMaker Debugger, custom conditions can also be created to test for specific behavior in your training jobs.

Why are we excited?

AWS SageMaker Debugger allows data scientists to iterate over a ML model to give better accuracy and assist in detecting model training inconsistencies in real-time. With a little brainstorming and experience, we can find out the actual problem in our ML model. It also integrates with AWS Lambda, which can automatically stop a training job when a non-converging action is detected, resulting in lower costs and faster training time.


Amazon SageMaker Debugger is now generally available in all AWS regions in the Americas and Europe, and some regions in Asia Pacific with additional regions coming soon.

If you’re looking to explore these services further and need some guidance, let us know and we’ll connect you to an Idexcel expert!

AWS re:Invent Recap: Amazon SageMaker Clarify

Amazon SageMaker Clarify

What happened?

AWS released Amazon SageMaker Clarify, a new tool for mitigating bias in machine learning model that helps customers more accurately and rapidly detect bias to build better solutions. This provides critical data and insights that increase transparency to help support analysis and explanation of model behavior to stakeholders and customers.

Why is it important?

  • Easily Detect Bias: SageMaker Clarify will help data scientists detect bias in data sets before training and their models after training.
  • Valuable Metrics & Statistics: It explains how feature values contribute to the predicted outcome, both for the model overall and for individual predictions.
  • Build Better Solutions: With the capability for developers to specify important model attributes, such as location, occupation, age, teams are better able to focus the set of algorithms in a sophisticated way to detect any presence of bias in those attributes. This enables teams to build the most accurate and effective solutions that drive client success.

Why are we excited?

With Amazon SageMaker Clarify, we can now better understand each feature in our ML models and give more detailed explanations to stakeholders. It provides transparency in model understanding that gives leadership more valuable information to inform critical business decision-making. SageMaker Clarify also includes feature importance graphs that explain model predictions and produce reports for presentations to better highlight any significant business impacts.


SageMaker Clarify is available in all regions where Amazon SageMaker is available. The tool will come free for all current users of Amazon SageMaker.

If you’re looking to explore these services further and need some guidance, let us know and we’ll connect you to an Idexcel expert!