Category: Robotics

How Chatbots Can Help Build Your Brand and Enhance Customer Service

In today’s cut-throat market, businesses leave no stone unturned to create a unique experience for their clients. And customer communication is the key to ensuring that your clients enjoy the same experience every time.

Customer communication should have to be prompt for marketing, sales, or support. If your business fails to offer smooth engagement, customers are less likely to stick with it. This is where AI-backed chatbots come in, as they help automate customer communication while reinforcing the support big time.

A chatbot is a software application that simulates human conversation via artificial intelligence. In the last couple of years, it has gained considerable traction, and it is now widely used in web-based applications, including internet apps, call centres, e-commerce, customer service and so forth.


Continue reading to understand how chatbots can help build your brand and enhance customer service:

  1. Chatbots are automated tools that enhance bidirectional communication. This results in better business outcomes with an improved customer experience and trust in the business.
  2. Advanced chatbots give a personalized human touch to conversations, with a welcoming message and an amiable tone – without the need for actual human intervention or risk of delays due to overloaded attention centres – which is a clear advantage for business consumers.
  3. Chatbots ensure faster response and immediate solutions to users, which makes customers feel more confident about the products or services of your company.
  4. Chatbots offer precise information on products, new launches, schemes, offers, official announcements, and other updates related to your services or products. This motivates customers to explore the services or products more and make well-informed decisions about their purchases.
  5. A chatbot designed to mimic human humour can make your brand more interactive, engaging, and livelier. Clients are more willing to talk to more human-like chatbots and respond with simple and fun messages.
  6. A chatbot represents your brand, and if it responds to customer messages instantly in your brand’s voice, your brand will become more valuable to your customers.
  7. A single chatbot has the potential to replace a couple of customer service executives, which helps reduce costs and save time substantially while providing customers with a consistent and seamless experience. This would help build a character for your brand, making it easier to gain customers’ trust.
  8. A chatbot on your website or social handles represents round-the-clock customer support. This is an excellent option in situations wherein customers are likely to lose confidence in your brand because no one was there to attend to them.
  9. Chatbots ward off human-specific restrictions in customer interaction. Typically, customer service agents manage just 2 or 3 customers at a time, but an intelligent chatbot doesn’t operate with such limitations. An intelligent chatbot can complement your human team while allowing your brand to reach out to more prospects in less time.

If you want to take your business to the next level in today’s digital era, chatbots are your way forward. We encourage you to connect with one of our specialists at Novatio, a leading RPA service provider, to understand how our custom automation solutions can help your business grow and thrive while preparing it for the future.

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Gokul Solai June 17, 2022 0 Comments

HyperAutomation in the Return to School Era

The following is a prelude to our more comprehensive piece on Hyperautomation in Education


Robotic process automation (RPA), sometimes referred to as software robotics, is a form of automation that’s about automating digital processes rather than physical ones. In other words, RPA isn’t about automating physical tasks like warehouse robots would do. Instead, you can think of RPA as a collection of mechanical minds that can save human experts from having to perform repetitive data entry tasks, processes that require interacting with multiple digital interfaces, or even some customer service business processes. While RPA is an important part of digital transformation across all industries, we’ve seen universities and other higher education providers use RPA to particularly great success.


Just as we’ve seen state and local governments embracing RPA during the COVID-19 crisis due to an increase in remote work, educators who face COVID-related challenges and the difficulties of remote learning are turning toward RPA. At Novatio, our mission is to help organizations find the RPA tools that make sense for their specific needs and make the transition as seamless as possible. Here are just a few great use cases for how higher ed is using RPA to their advantage and how we can help.


Application Processing

One of the greatest challenges higher education providers face during peak seasons is the influx of new college applications. This has been compounded for top colleges, which are actually seeing a significant increase in admissions during the COVID-19 crisis. Using legacy systems, human workers would have to manually read each application and check it against college requirements. With RPA, however, it’s possible to set up machine learning software bots that understand the parameters for high-quality applications, and these software bots can automatically process them.


An RPA bot can do this by automatically checking the courses each student is applying for and comparing their accomplishments to the prerequisites for the courses. This way, eligible students can be moved on automatically, and staff members can be flagged if a promising application lacks a necessary prerequisite.


Course Scheduling

RPA implementation in higher education facilities goes well beyond streamlining admissions. Course scheduling is another challenge that higher ed facilities must contend with each semester, and it requires collaboration between multiple different departments. Using legacy systems, each department will likely have its own data sets, and they have to manually share data with each other to determine the most popular course times for student demographics.


With robotic process automation, it’s possible for different departments to pool their data, and automated data analytics systems can check data between different courses and student information to determine the ideal times to hold each course. This improves the student experience, and it makes things much easier on the faculty, especially if your school struggles with scheduling. Naturally, this solution can be applied to other scheduling matters as well, such as sports, clubs, and other activities.


Financial Reports

Naturally, the COVID crisis has brought financial hardships to most sectors, and higher education isn’t any different. It’s estimated that 74% of colleges are now facing financial hardship, and it isn’t difficult to see why. Outside of the top colleges, enrollment is declining as students take breaks from education, and the decrease in state funding over the years has done nothing to help public higher education facilities.


RPA can help reduce costs in financial planning and processing by automatically collecting actionable insights backed by big data, so you’ll have everything you’ll need to plan accordingly for each semester. Of course, it isn’t just about keeping up with tuition costs and student spending. Intelligent automation can also help you process FAFSA applications, just as it helps you process admission applications. Determining eligibility criteria for each FAFSA form is incredibly time-consuming, but if you can set up software bots that understand the parameters for eligibility, you free up your staff to focus on core financial concerns.



A chatbot is basically a virtual assistant that can simulate a real human conversation. While you naturally want to keep human assistants on hand for complex inquiries, many simple questions can be answered by a chatbot on your school website. With the help of natural language processing, these bots are able to understand questions submitted in a conversational tone, and they can provide accurate answers to questions regarding admissions, scheduling, and financial aid from students, family, and staff.


Processing Grades

Faculty members have to keep up with student reports which are collections of a student’s grades, recommendation letters, their academic program(s), and everything else to do with their time in college. Certain updates, like writing and adding new recommendation letters, may require manual steps, but grade processing can be automated.


Most teachers already use a learning management system to automate tasks with grade processing, such as having formulas that calculate each individual student’s average, for example. Once final grades are recorded after the exam, RPA makes it possible to pull each student’s grade from their teachers’ learning management system, so it can be instantly added to that student’s report without any manual tasks being performed.


These are just a few excellent use cases for RPA in higher education. We’re here to make sure you get the functions you need with reliability and scalability to ensure you see a good return on investment. Whether you need artificial intelligence solutions for student servicing or to simply automate some database functions, we can get you started with some quick wins for your efficiency and your return.

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Gokul Solai February 17, 2022 0 Comments

Happy Valentine’s Day Robo Dog!

One of the cutest commercials from the Super Bowl involved Robo Dog and the new electric Kia Car. Robo Dog is envious of his real-world counterparts’ relationship with humans, so he leaves his storefront perch to pursue the same relationship with the driver of the electric Kia (


Robo Dog’s persistence and loyalty are clearly on display as he jumps from rooftop to rooftop to track down his potential new owner. The commercial climaxes when Robo Dog leaps off a rooftop towards his new owner, only to run out of batteries mid-way. The screen goes blank, and then we see the owner saving Robo Dog’s “life” by charging him back to “health” with his Kia.  The commercial concludes, and we are led to believe a lifetime relationship of compassion ensues.  Robo Dog is super cute, and no doubt this was my favorite commercial from the Super Bowl. But could I love a robotic dog? It’s not too far from a real scenario as humans and technology are symbiotically tackling obstacles in the workforce and socially. IoT Technology is helping citizens remain healthier by monitoring their health.  Multiple intelligent automation solutions help humans work more efficiently to get home to their families earlier. Conversational AI can even talk to humans to help them receive vital aid.  These examples show that technology can Touch (IoT), See (computer vision), and hear (conversational AI) for us. But can it replace the sense of love?Even the technologist in me is highly skeptical that Robo Dog could replace my love for dogs. But I can imagine Robo Dog being involved with my family in several ways — helping my kids study, running simple tasks for us, and keeping us safe at home — all things my mini golden doodles struggle to do.  If Robo Dog were only $299 as he is in the commercial, an amazon drone would drop him at my doorstep this morning.Until then, back to showing our love with flowers, balloons, and fixed price dinners

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Gokul Solai February 14, 2022 0 Comments

AI Cannot Think for Us, But It Can Work for Us

The Symbiotic Relationship Between Humans and AI


When we say AI thinks “like a human,” we really mean that it thinks “similar to a human.” There are many key differences between our biological neural networks, and artificial neural networks.
In our last article, we discussed the similarities in neural networks which are modeled after human brains and how that benefits our data training and labeling needs. However, we did not talk about what makes this technology different from how we work.


AI Is an Imitation

Artificial intelligence may never think in the same way humans do, as AI is not “thinking” at all. There are inherent differences between human intelligence and machine-learned intelligence that will prevent this, such as the inability to think uniquely, or past what the system has been taught to do. 


In fact, a top researcher of Artificial Intelligence wants people to stop referring to AI as “Machine Learning” in general. Michael I. Jordan, a professor at the University of California, Berkeley, asserts that most AI systems are nowhere near the capabilities of humans, as they are simply showing the most basic levels of pattern recognition skills. 


That being said, these differences do not inhibit the technology. While the terms artificial intelligence and machine learning can be a bit overused, AI can certainly be very intelligent and has the capacity to learn. Although there are some processes that AI cannot do better than humans, there are also processes where technology will beat us every time; and these things are improving at a rapid rate. 


AI Is an Extension of Its Creator

A U.S. federal judge recently ruled that AI cannot be classified as an inventor on a patent. Rather, the creator or owner of the AI is listed as the inventor. After all, the owner of the AI was the one tweaking algorithm, overseeing the data labeling and training.


The purpose of AI in the present and future is not to replicate human intelligence or replace the role of humans. The purpose of artificial intelligence is to create a self-teaching system that enhances the capabilities of humans.


The Future of AI?

So, humans and AI will always be distinguishable from one another. (Sorry Bladerunner fans.) But we’re still curious. What does the future of AI look like? 


AI is already used to create self-driving vehicles, analyze vast quantities of data, diagnose and treat illnesses, enhance customer retail experiences, and much more. 


Many experts predict that these uses will be expanded and improved upon, so much so that AI will be able to overcome the obstacles created by the biological limitations of humans. For example, AI could conduct long-range space expeditions to colonize other entities within our solar system without risking human lives, or even fight climate change using atmospheric drones. In fact, Microsoft has already begun using artificial intelligence to fight climate change through their “AI for Earth” program.


Artificial intelligence also has huge potential in future workplaces. AI could be used as a decision-making tool for companies, helping improve customer service systems and support management positions. To learn more about how technology like RPA and AI are already improving the workforce, read our blog The Factory Metaphor.


Again, AI will work alongside human workers, assisting us where we fall short, but never taking over completely.  In the future, we see a world where humans and Artificial Intelligence evolve together and AI has a metaphorical hand in most aspects of life. But unique decision-making and problem-solving will always set us apart from our robot counterparts.


If you are interested in implementing technology like AI, RPA, or ML into your workflow, contact us. Together, we can improve the way we work alongside artificial intelligence and drive the future of this technology.

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ZYPE Digital Agency November 2, 2021 0 Comments

The Factory Metaphor

5 Steps to Ensure a Return on Investment From Your RPA

Each year, more and more organizations across the world are looking to automate their processes. A 2020 study done by McKinsey & Co. shows that 66% of businesses have taken steps toward automation. RPA (Robotic Process Automation) is leading this trend.

With top RPA providers like UiPath, which recently became the 3rd largest tech IPO in U.S. history, automation has become mainstream, and experts believe there will be an even larger uptick in the utilization of automation tools like RPA.

To fully understand RPA, and to use it to your company’s full advantage, you need to not only understand what RPA is, but how it fits into the larger automation ecosystem and how it fits into your business infrastructure, too. For those of you who are new to intelligent automation, some terms of reference are included at the end of this document.

So, how do we simplify RPA so we can start using the technology effectively? We can start by comparing it to something we can all relate to—a factory. 

RPA Simplified

Imagine you are a manufacturer who is looking to speed up the assembly of one of your products. You do the research and finally decide to invest in a new piece of equipment that will improve productivity significantly.

After implementing the new equipment, you are disappointed to find that the overall effect it has on your productivity is much less impressive than you expected. The efficiency and/or output of the product line that’s been automated may have improved, but the production rate of the entire operation has remained static. It feels as though your investment has fallen short.

You may have the same reaction when you first begin exploring RPA. But the issue is not with the technology; it’s how you use it, scale it, and manage it.

Process Selection

When you are choosing a new piece of equipment to improve the production of your factory, you don’t (or shouldn’t) start your search with the equipment, but with the process you are trying to improve.

For example, you may notice that there are two processes slowing your factory down: (1) The assembly of a complicated part that is ordered once a month and (2) the daily packaging of the products you ship. Both processes are time-consuming, but one is the obvious candidate for a new machine—the process that affects a wider range of your products, more frequently. And so, your search for a boxing machine begins.

Process 1 is time-consuming, but specific and performed less frequently. Even though it is tedious when performed, investing in automating it will have less of an overall impact on the operation as a whole.

Choosing the right process is not always black and white. The best approach is to look at the impact it will have on your organization’s overall workflow. That means carefully considering the bigger picture prior to committing to a specific piece of equipment, no matter how promising it seems.


That new boxing machine you purchased may have the potential to streamline your production line, but only if your staff knows how to use it. Without knowledge of how the machine works, it can’t be used to its full potential, and may end up sitting in the corner of your factory gathering dust.

Just like a boxing machine, RPA is not impossible to understand, but it does require some training. However, with the proper training, the equipment can be empowering, giving you more time to focus on the processes that matter. Having an understanding of the technology is the first step in making the most of RPA.


All machinery requires maintenance. Even the newest, most innovative boxing machine will eventually need a tune-up, replacement part, or cleaning in order to keep functioning properly. Sometimes, this maintenance can be done by internal staff members. Other times, you may need to hire out. Either way, being prepared for necessary maintenance after implementing the machine is going to be essential to keeping the factory running smoothly.

Your IT department has to be prepared, too, in case your RPA software needs troubleshooting, updating, or maintenance. After you implement the software, your business process will adapt to that software, and become reliant on it. Being equipped to get it up and running again in case of emergency will give you and your team peace of mind.


Once you’ve decided on and implemented the best equipment for your factory, it’s time to see where else automation can bring efficiency.  A good place to start is looking at similar processes on other production lines. Soon, you will see the productivity of your factory skyrocket, and your return on investment will multiply. The best outcomes occur when scalability is considered from the outset.

It’s important to remember that scalability is not just about growth, but optimization. The results of the boxing machines may be great, increasing your production speed substantially. However, without a plan, operational issues can occur. For example, the increased production creates more inventory than you can handle. As a result, you sell your products for a reduced price, and the investment is no longer profitable.

Your RPA must align with your business’s infrastructure. You want to make sure you do not outgrow your resources. Automation isn’t a “set it and forget it” solution. It only works when it is constantly measured and continuously improved.


In Novatio’s recent article on governance, we define it as a way to “establish roles and responsibilities, decision points, alignment processes, communication, and performance metrics” in order to successfully manage your RPA software.

Just as you hire employees whose goals align with those of your organization, you must also ensure that the RPA software you choose aligns with those goals, too. Furthermore, you must make sure that the software continues to align with your goals after implementation. That’s where governance comes in. Unlike your employees, RPA governance is different from traditional governance—it has to be much more adaptive and flexible. This requires something in addition to IT support or employee training; it requires an RPA leadership team. To learn more about what that takes, click here.

The Takeaway

Implementing an RPA software successfully is an ongoing process but following these 5 steps will get you there quickly and effectively. Studies have shown that businesses who properly implement RPA can see up to a 4X return on their investment. Don’t let your RPA fall short.

Be on the lookout for future blogs that will dive deeper into each of these steps to help you find success on your RPA journey. In the meantime, contact Novatio for assistance getting started with RPA, finding the right processes, or improving any of the areas we talked about.

Terms of Reference

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How Robotics Process Automation Dominates The Insurance Industry?

RPA or Robotic Process Automation has been dominating the insurance industry for years. It can capture all manual steps performed by an employee to login to the software, looking for documents, and enter details, etc.  In the article, we will discuss the best practices to implement RPA for insurance processes and how RPA can help you in crucial insurance processes?. Moving ahead, we will let you know how RPA is different from AI and process for document digitization in Insurance.

1. RPA to Process Claims

RPA can copy data from one source to another, and data appears the same at both the sources. Claim adjusters must collect the relevant data from clients, hospital, or police so that the right decision can be taken how much they need to pay out to settle down the claim.

Once all necessary data is collected from different sources, it should be translated into meaningful information to produce the digital record of the incident. Using RPA, it is easy to go through all the records, process them, and make a final decision based on your findings.

2. RPA for Underwriting

RPA can collect the information from different sources to a single location. Underwriters will evaluate potential risks that customers, their cars, and homes pose to the insurance carrier. However, the information they need in underwriting varies based on the objective.

3. RPA software implementation in the Insurance Industry

RPA software system has to be revamped as soon as some changes occur to internal or external data sources. RPA does not work alone, but it has to be integrated with the existing infrastructure or legacy system. Sometimes, there is a need to modify infrastructure as well for successful implementation of the RPA software program without any failure.

However, RPA can be the wrong choice for processes changing frequently, but AI is the best option to adopt in the case of unpredictability.

4. RPA vs. AI: How are they different?

RPA solutions can be combined with AI capabilities, but they are two different terms. AI is the process to improve the accuracy of the output of a process over time, but it is not possible through RPA. It can scale processes but cannot improve or make them smarter later.

5. Document Digitization

Besides analyzing data from various external sources, insurance companies have to manage internal data too stored by their employees. Mostly, insurance claims are still filed on paper, and employees have to fill the data manually to the CRM system. RPA alone is not enough in digitizing documents, but it should be clubbed with AI features for automating this tedious data entry.

The discussion makes it clear how RPA is just an amazing solution for automating processes in the Insurance Industry. Every place where lots of data is released daily, and it has to be stored and analyzed for future references, RPA can work magically for those industries. All the best for a successful implementation of RPA software products in your Insurance Company.

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September 19, 2019 0 Comments

Buy a Home From A Robot? AI Wants to be Your Real Estate Agent

Part 1: Intelligent Listings

You’ve probably heard of artificial intelligence in self-driving cars and phones, but did you know AI is also breaking into the real estate sales market?

Similar to how Facebook and Netflix use online customer behavior, real estate platforms are now adding targeting features to sell you the perfect home!

In this two-part study, we look at the benefits of using AI in buying, selling, and automating agent administrative tasks.

AI in Buyer Targeting

There are generally two ways individuals search for homes in today’s real estate market. The first is to contact a real estate agent who walks you through the search and buying process and then takes a 5-6% buying fee. The other is to tackle the search process on your own through online listings such as Zillow, Trulia,, and Redfin. Even so, a real estate agent is generally required for open house tours, negotiations, and contact closings.

But buyers’ options are growing. New companies are using AI are guessing you’d rather conduct your home search on a computer for a lower buying fee of 2-3%.

In fact, that’s exactly what the new AI company, REX, does. The AI company has a sourced database of homes looking to sell to consumers. Using techniques such as geographical radius, past buying behavior, recent life stages, and online presence, REX targets ideal buyers with ads on websites and social media.

It is even able to identify data nuances that real estate agents would not have access to, for example: homes in a certain area within a walking distance of a Starbucks tend to sell for 3-4% higher than other homes.

It is these types of data on the real estate market, home features, and customer’s online behavior that has allowed REX to sell 231 homes since its start in 2016.

AI in Customized Listings

So can the standard listing platforms such as Zillow and compete with AI companies like REX? How can they battle low buying fees and targeted listings? With the help of artificial intelligence, they are changing the way their homes are sorted and displayed to buyers.

Zillow is investing heavily in AI for its search, home recommendations, and tracking customer click behavior. This process is called Personalized Sort and it is one of the key ways the company is trying to distinguish itself from the other online real estate platforms.

I Not much has been revealed about Zillow’s new AI program, which will roll out soon, but it plans to take the “heart” button to the next level. Many of these online listing websites already have interactive elements, such as a “heart” button for favoriting homes. When a user hearts a property, it saves in your personal account, allows real estate agents to measure interest, and prompts email reminders about the property to the buyer.

Consider the possibility of allowing the user to heart certain aspects of home attributes. This feedback could be stored in their account and allow the program to generate similar homes matching those favorite characteristics. If a Zillow customer is searching in a particular neighborhood and continuously shows an interest in certain home features — year built, porches, granite countertops, new roof — the artificial intelligent system learns and displays other homes with similar accents.

In addition, Personalized Sort also will take into account non-home preferences with its recommendations, like school districts, movie theaters, and vicinity to local parks.

“No industry is untouched by the potential power of intelligent data,” says Gokul Solai, Novatio Solutions CEO. “It will be interesting to see how quickly competitors catch up to leaders in the industry who are embracing what AI can do for them.”

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June 28, 2018 0 Comments

Robot, Mans Best Friend

After years of data privacy battles in the legal world, I recently embarked on a “career upgrade” to the role of General Counsel for a startup company that implements digital robots.  At first, I was not convinced. The business of digital robots is not remarkably litigious, but I came from a world where most data breaches and legal issues are highly regulated and scrutinized down to the very letter of the law.  Now, I operate in an unregulated world where both “people problems” and “robot problems” can often transpire into legal problems. Thus, I spend most of the day as wearer of multiple hats (along with Jack, who boasts many traits as well).  Anything is fair game as lead counsel.  Gone are the days when I could simply escalate to someone above my pay grade (the buck always stops here). But these are the woes of any General Counsel, which is not the purpose of this article. The purpose of this article is the one point that has become clear in my new role: the data privacy battle is much easier to fight with digital robots in your corner.

This became especially apparent to me in the wake of the recent Facebook/Cambridge Analytica news. The big scandal and all the frenzy — it all came down to one person:  Aleksandr Kogan, University of Cambridge researcher who created the personality quiz app called thisisyourdigitallife.  In a world where some of us need an app to tell us our personality types, we absolutely must have someone to tell us the data we provide is safe.  And that’s exactly what Facebook did in its 8 page microscopically-lettered privacy policy and terms of service which no one cared to read.  The data that was breached was not obtained against Facebook’s terms of service and there is no argument that the data was obtained illegally.  But it was against Facebook’s terms for Kogan to hand that data to another firm.  Initially, when news of the breach broke out, both Facebook and Cambridge Analytica seized the opportunity to point fingers at Kogan.  He was a bad actor, a criminal. And the rest of the system remains unflawed but for the acts of this one individual. It’s a stretch, but this was the position.  But shouldn’t our system account for the acts of individuals such as Kogan?  Shouldn’t we assume that there will be such bad actors?  Although Facebook quickly changed its tune to take blame for the incident, with Zuckerberg apologizing to the public for about the 87th time, it is undeniable that these types of leaks or breaches happen at the hands (literally) of those in the tranches with access to way too much information.

It’s not just Kogan, it could be me or you or anyone else with solid education who just woke up one day making an extremely bad judgment call. But digital robots, on the other hand, don’t wake up having bad days. They’re not financially motivated and don’t make decisions based on self-implication. They follow rules and you can trust they will not engage in the typical office banter of whether we should make America great again. Extremely accurate with undeniable loyalty, they will never talk back. If you think about it, these are the qualities we should be looking for in today’s workforce. Instead of pointing fingers at bad actors such as Kogan, we should minimize the need to rely on people for certain tasks (since people undeniably include bad actors). Of course, digital robots have their limitations in that they operate in a rules-based manner, being extremely black and white. But with machine learning capabilities nowadays, we are able to train digital robots to execute and process tasks similar to how a human would. The real fear is one you’ve probably heard many times, the age-old debate about robots replacing humans, which is addressed head-on by our CEO, Gokul Solai, here. The other, less realistic fear, is robots taking on an Artificial Intelligence evolution that ends much like the movie, The Terminator. The day that happens, it looks like we will all be ready for another “career upgrade”.

Interested in finding out more about digital robots? Explore Novatio Solutions

Written by: Sumitha Pitroda,Vice President and General Counsel at Novatio Solutions

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May 4, 2018 0 Comments


By now, we’ve all heard or seen the doomsday predictions of evil robots taking over the world. From tech billionaire Elon Musk to Stephen Hawking have warned of a dark future with artificial intelligence. But not all AI is bad for humans.

Here are four ways that artificial intelligence robots are helping humanity today and should continue to do so as technology advances.


The lifespan gap between the richest 1% and poorest 1% has widened almost three years since 2001. Wealthier men now live 15 years longer than their poor counterparts. The gap is 10 years for women.

Many factors contribute to this widening gap – access to better nutrition, healthcare, and more education on harmful and beneficial behaviors (like smoking and exercise). Wealthier people also often benefit from a support team – chefs, personal trainers, doctors, nutritionists – to motivate and inspire them to positive lifestyle choices. What if everyone had access to a team like that?

Artificial intelligence and other technologies are bringing wellness and self-care coaching to a broader audience. Through smartphone apps, telemedicine, fitness trackers, and other tech, healthcare is being revolutionized and democratized like never before.

One example, the Yoo-Mi assistant, uses AI to “understand and empathize” with individuals, customizing information, motivation and guidance to a person’s unique psychological make-up. The goal is to be the support team for everyone, regardless of income, and help people live longer, healthier lives.


Tech educators are using virtual programmable robots to teach kids the fundamentals of software coding. After introducing them to basic concepts of writing commands, the folks at Free Code Camp hold tournaments where teams of kid coders compete against each other and their robots.

The kids who participate have the freedom to create robots that can do different tasks, like mining for resources or finding and fighting other robots. And they use creative problem solving to use those robots to accomplish objectives set by the camp staff.

Once they have learned coding principles, Camp educators create new challenges – like creating a new alarm clock and other real-world scenarios.

“When we gave kids the task to create a new alarm clock, they came up with some very creative solutions,” said Tim Großmann. “Many of which would appear really weird, at least to us.”

“There were many times when I thought I couldn’t have come up with their solutions,” he added.


We can think of physically-demanding jobs: construction worker, landscaper, firefighter. But other professions are more demanding emotionally and can cause workers to suffer from burnout.

Professions like customer service representatives, flight attendants, doctors, nurses, school teachers, and hotel employees require the suppression of true emotions for the sake of the job. In many cases, these professions mean taking verbal or emotional abuse from the people they serve without responding in kind or venting their frustrations. Over time, this can be extremely draining.

Technology, and specifically artificial intelligence robots, can help ease the daily burden professionals in these careers face in two ways. First, chatbots and other AI platforms can act as the first line of customer service. Second, virtual therapists or companions can give professionals an emotional outlet.

“In the future, robots may serve in a variety of support roles, such as home assistance, office support, nursing, childcare, education, and elder care,” said psychologist Gurit Birnbaum.

Many experiments, including ones made by psychologists like Birnbaum, have shown humans are open to making emotional connections with robots — both as customers seeking help and exhausted service professionals looking for support.

“Anywhere you have people doing emotional labor, there could be a potential for this technology to serve that role without incurring the negative effects on a worker’s health,” said computer scientist Jonathan Gratch.


The movie makers at Disney’s Pixar have a tapped into the power of AI to lighten their animation loads. Even with the help of modern technology and rows of powerful computer servers, some scenes can take hundreds of thousands of hours and films years to finish.

Researchers at three organizations partnered to develop new deep learning artificial intelligence technology to improve frame quality. Using millions of images from 2016 film “Finding Dory,” the team trained the tech to recognize and sharpen fuzzy, grainy (“noisy”) images.

“Other approaches for removing image noise have grown increasingly complex, with diminishing returns,” said Markus Gross, vice president for research at Disney Research. “By leveraging deep learning, this work presents an important step forward for removing undesirable artifacts from animated films.”

The AI algorithm allows artists to quickly and automatically remove noise, while making sure they keep scene detail. Disney and Pixar plan to use the technology in their upcoming films to shorten the movie-making timeframe. In a bid to continue to the forward push of research, they are even making the code available to the research community.


Contact our experienced team to learn how a digital workforce can improve your business processes.

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April 2, 2018 0 Comments

RPA: Year In Review

Year In Review & Look Into The Future

Artificial Intelligence (AI) technologies like Robotic Process Automation (RPA) and machine learning are the biggest
disruptors in global business since the Internet. They are transforming work by stripping away mundane, repetitive
tasks and freeing up people to handle more advanced, innovative work.

Read the full blog post, here.

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December 8, 2017 0 Comments