Tag: Customer Service

Dev, can you start by sharing the journey that led you to establish QueryPal and what inspired you to focus on transforming customer support through AI-powered ticket automation?

The journey to QueryPal began with my experiences at Google and PayPal, where I saw firsthand the challenges of scaling customer support. I realized that while AI was transforming many industries, customer support remained largely unchanged. The inspiration came from seeing how Large Language Models (LLMs) could understand and generate human-like text. I knew we could leverage this technology to revolutionize customer support, making it more efficient and effective. QueryPal was born from the vision of creating an AI system that could understand customer inquiries at a deep level and provide accurate, helpful responses at scale.

How has AI enhanced the accuracy of customer support responses at QueryPal, and what role does it play in improving response times and customer satisfaction?

AI has dramatically enhanced the accuracy of customer support responses at QueryPal. Our advanced natural language understanding allows us to comprehend the nuances of customer inquiries, including context and intent. This leads to more precise and relevant responses. Moreover, our AI can access and synthesize information from vast knowledge bases in seconds, providing comprehensive answers faster than any human could. This improvement in both accuracy and speed has led to significant increases in customer satisfaction scores for our clients. We’re also in the early stages of researching Causal AI, which could enable our system to understand cause-and-effect relationships in customer issues, potentially allowing it to reason about novel situations it hasn’t explicitly seen in training data.

Personalized customer support is a significant advancement in customer service. Can you explain how AI-powered systems at QueryPal tailor responses to individual customer inquiries?

Personalization in QueryPal’s AI system operates on multiple levels. First, it considers the customer’s context, including channel metadata. Second, it analyzes the specific language and tone of the current inquiry. Finally, it takes into account how past responses for similar questions have satisfied customers. By combining these factors, our AI can tailor responses that not only answer the specific question but also address potential underlying concerns, use appropriate language and tone, and even anticipate follow-up questions. Personalization in QueryPal’s AI system is already advanced, but we’re excited about the potential of Agentic AI. We’re in the process of integrating this technology, which could allow our system to handle complex, multi-step tasks with minimal human specification. In the future, it might be able to understand the broader context of a customer’s journey, anticipate needs, and even take proactive steps to resolve issues before they escalate.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-dev-nag/

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Have you encountered a bad situation that was made worse by something that is meant to help? Here’s a recent example of mine – I had to take my son to an emergency room while vacationing in Asia but the most frustrating part was dealing with insurance when we got home. The agent who initially processed my claim put me (and my money) in limbo – no external or internal follow-up communication, inaccessible and invisible in the client portal – because they didn’t follow the process for handling non-English documents. This poor customer service was entirely preventable and, though I’m not an insurance industry expert, I’m going to tell you how.

I started this article with my personal experience because all service providers need to consider customer impact when designing their AI adoption. Unfortunately for me, health insurance is a relatively inelastic service. The insurance company – let’s start to see ourselves in their position now – has many customers locked in for the year irrespective of individual satisfaction. It also means that customer acquisition is relatively fixed. Insurance companies are not alone in having profit margins that are won and lost in processes. They’re also not alone in having a customer base that includes stubborn engineers who will spend above-average time investigating problems to discover a root cause (hi, that’s me). Even though I can’t switch medical insurance, the original agent’s mistakes followed by my persistence led to an undesirably high touch time for the insurance company (getting personal again, I digress…)

Whether your organization manages insurance claims, manufactures automotive components, or facilitates the food and beverage supply chain, profitability is influenced by how well your people, processes and systems are harmonized. Fortunately, some of the up-and-coming solutions embedded with AI have started to measurably improve the balance with people, processes and, ultimately, profit. One of the solutions with a high yield potential from relatively low effort is called Process Mining. Gartner defines it as “a technique designed to discover, monitor and improve real processes (i.e., not assumed processes) by extracting readily available knowledge from the event logs of information systems”. What gives process mining the potential for high yield with low effort is that it leverages information that your business processes already generate but traditionally ignore outside of IT troubleshooting. Process mining users are provided with unprecedented visibility of process flows and deviations. Analysis of those deviations turns into data-driven continuous improvement with the possibility of incorporating process improvements that were already proven through execution even though they weren’t pre-planned.

To Know More, Read Full Article @ https://ai-techpark.com/ais-role-in-process-mining/

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How AI avatars are transforming customer service in business

What hasn’t AI transformed? Many business fields have evolved in recent years thanks to the tools that Artificial Intelligence has provided, one of them is customer service, through the use of AI avatars.

This is a new way in which companies are interacting with their public, trying to be more efficient and sophisticated in their processes. AI avatars are a very interesting figure in this transformation of customer service, as they have allowed companies to interact with their customers in a more personalized and efficient way than ever.

These virtual assistants are equipped with natural language processing and machine learning technology, which has redefined the customer experience by providing faster responses, solving problems more accurately, and even anticipating potential customer needs.

In this article we will delve deeper into the topic of AI avatars, how they are changing the rules of the game in customer service and what they bring to today’s modern companies.

Let’s start with the basics: What is an AI avatar?

When we talk about an AI avatar, we refer to the virtual, dynamic and animated representation of a person through Artificial Intelligence to interact with users in an automated and personalized way.

These avatars have the ability to simulate a human conversation, answer questions, provide assistance and solve problems, without the need for direct human intervention.

The digital avatar market is growing considerably

Everything indicates that the strategy of digital avatars is not a passing fad but is here to stay and grow constantly. According to a report by Spherical Insights, the global digital avatar market size is expected to reach $283.47 billion by 2032, a clear sign that businesses are increasingly investing in this tool.

“Technological advances in 3D modeling, animation and rendering result in increasingly realistic and visually appealing digital humans. Conversations become more attractive and closer because these avatars can look very similar to humans,” they noted in another report from the Market Research Future portal.

In this report they also indicate that the main market that uses AI avatars is North America, driven by the launch of new products and expansions of others, which has increased the need for this virtual assistance. Likewise, the Asia-Pacific region is the fastest growing region in terms of AI avatars, which is very promising for the immediate future.

To Know More, Read Full Article @ https://ai-techpark.com/transforming-customer-service-with-ai-avatars/

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Leslie, can you please introduce yourself and share your experience as a CEO and Founder at TurinTech?

As you say, I’m the CEO and co-founder at TurinTech AI. Before TurinTech came into being, I worked for a range of financial institutions, including Credit Suisse and Bank of America. I met the other co-founders of TurinTech while completing my Ph.D. in Computer Science at University College London. I have a special interest in graph theory, quantitative research, and efficient similarity search techniques.

While in our respective financial jobs, we became frustrated with the manual machine learning development and code optimization processes in place. There was a real gap in the market for something better. So, in 2018, we founded TurinTech to develop our very own AI code optimization platform.

When I became CEO, I had to carry out a lot of non-technical and non-research-based work alongside the scientific work I’m accustomed to. Much of the job comes down to managing people and expectations, meaning I have to take on a variety of different areas. For instance, as well as overseeing the research side of things, I also have to understand the different management roles, know the financials, and be across all of our clients and stakeholders.

One thing I have learned in particular as a CEO is to run the company as horizontally as possible. This means creating an environment where people feel comfortable coming to me with any concerns or recommendations they have. This is really valuable for helping to guide my decisions, as I can use all the intel I am receiving from the ground up.

To set the stage, could you provide a brief overview of what code optimization means in the context of AI and its significance in modern businesses?

Code optimization refers to the process of refining and improving the underlying source code to make AI and software systems run more efficiently and effectively. It’s a critical aspect of enhancing code performance for scalability, profitability, and sustainability.

The significance of code optimization in modern businesses cannot be overstated. As businesses increasingly rely on AI, and more recently, on compute-intensive Generative AI, for various applications — ranging from data analysis to customer service — the performance of these AI systems becomes paramount.

Code optimization directly contributes to this performance by speeding up execution time and minimizing compute costs, which are crucial for business competitiveness and innovation.

For example, recent TurinTech research found that code optimization can lead to substantial improvements in execution times for machine learning codebases — up to around 20% in some cases. This not only boosts the efficiency of AI operations but also brings considerable cost savings. In the research, optimized code in an Azure-based cloud environment resulted in about a 30% cost reduction per hour for the utilized virtual machine size.

To Know More, Read Full Interview @ https://ai-techpark.com/ai-tech-interview-with-leslie-kanthan/ 

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The rise of Generative AI (GenAI) has enormous potential for the banking and finance industries. By utilizing GenAI, banks and credit unions speed applications from submission to approval, save time and effort, and deliver a desirable customer experience.

A recent report from the Society for Human Resource Management (SHRM) and The Burning Glass Institute details how GenAI will have an outsized role on the banking and finance industries. The report lists Morgan Stanley, Bank of America and Northwest Mutual as some of the organizations that are most likely to capitalize on the implementation of GenAI. Their study also measures GenAI exposure among several different professional industries; “investment banking and securities dealing and brokerage” measured third highest while “mortgage and nonmortgage loan brokers” ranked highest overall. If SHRM and The Burning Glass Institute are so convinced that GenAI will profoundly alter how financial institutions operate, what will that change look like and why does it matter?

GenAI is distinct from other forms of automation by its ability to automate what is typically considered knowledge work. This represents a sea change in how professional industries, including financial services, will implement automation technology in their workplaces. In fact, financial services are especially dependent on repetitive manual processes requiring specialized knowledge. Processes like loan underwriting and credit card applications require knowledge workers to manually input data and individually connect with customers or members, which takes up the majority of workers’ time and tasks.  GenAI excels in automating repetitive, manual tasks—such as data processing and pattern identification—streamlining operations and freeing up valuable time for knowledge workers.

The applications of GenAI within financial services manifest in both evident and nuanced ways, each offering distinct advantages to forward-thinking institutions. Many industries have begun employing GenAI solutions as chatbots for customer service, and financial services are no exception. GenAI-powered chatbots, operational around the clock, offer an immediate response to customer inquiries, significantly reducing the need for direct intervention by skilled professionals and enhancing service efficiency.  However, these solutions become even more compelling for financial institutions when embedded in the bank or credit union’s broader systems. For example, a loan applicant can interact with a GenAI-enabled chatbot and get a real-time status update on their loan status by providing a few identifying details. In this way, GenAI increases efficiency while also directly improving the customer or member experience.

GenAI technology is novel, and its implementations are sure to evolve further in the coming months and years. However, its potential for financial services is undeniable. In order for banks and credit unions to take full advantage of this nascent technology, financial institutions need to create AI policies, complete digital transitions and start exploring and investing in GenAI use cases now.

To Know More, Read Full Article @ https://ai-techpark.com/how-generative-ai-enhances-credit-unions-and-community-banks/ 

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What is your vision for the future of robotics and its potential to further transform industries, education, and society as a whole?

Robotics has significant transformative potential. They will make industries more efficient and adaptable, introducing new business models and changing how sectors like healthcare and manufacturing operate. Robots can address challenges like elder care and urban efficiency.

They can also offer students hands-on learning, making education more tailored and effective. It’s not just about learning robotics; it’s about learning with them.

My vision for the future of robotics includes machines working alongside us, specifically in a more inclusive, equitable, and innovative world where technology amplifies the best of human capabilities.

Can you please provide a brief overview of RobotLAB and its significance in the field of robotics?

Since its founding in 2007, RobotLAB has provided turnkey robotics solutions to companies of all sizes in industries including foodservice, hospitality, banking, education, assisted-living, education, cleaning, delivery and hospitals. Our talented team of roboticists has effectively deployed thousands of robots that have provided businesses with a clear path to the successful and highly specialized integration of robotics solutions.

As labor becomes increasingly expensive and scarce, we help businesses harness the power of robotics to improve bottom-line and employee retention by reallocating routine tasks to automated technologies. Our team oversees all aspects of the robotics integration process – from sales, tailored programming, on-site integration and repairs – to ensure businesses can access and understand solutions that will dramatically improve their performance. To improve the availability of robotics access nationwide, we recently launched a first-of-its-kind robotics integration franchise opportunity in 40 U.S. states, with the remainder set to clear before the end of 2023.

How do you see the relationship between humans and robots evolving as technology continues to advance?

As technology advances, the relationship between humans and robots will become more collaborative. Robots are tools, designed to enhance human capabilities. As they become more integrated into our daily lives, they’ll be seen less as distant machines and more as extensions of our own capacities.

In education, for instance, robots will serve as learning aids, making educational experiences more personalized and interactive. In industries, they will work alongside humans, taking on repetitive tasks and allowing us to focus on more value-added activities.

Elad Inbar is the founder and CEO of RobotLAB, a unique company dedicated to making robots smart and useful in multiple industries, including education, hospitality, restaurants, hotels, assisted living facilities, etc. His current ventures in robotics and education have received wide publication and recognition in Time Magazine, The New Yorker, Tech Crunch, IEEE, NBC, Financial Times, Fast Company, CNET, San Francisco Chronicle and other media outlets. He shares his experience as a keynote speaker in many events such as SxSW, National Restaurant Association, Florida Lodging and Restaurant Association, and TCEA, ACTE, FETC and many others. Elad also sits on the Forbes Technology Council.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-elad-inbar/

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AI and ML are changing the way we live and work. Many people think they’re reserved for tech giants, however. But increasingly we’re seeing SMEs harness the power of these tools. And the benefits are clear: artificial intelligence and machine learning can improve operations, boost customer satisfaction and help companies to outpace the competition – all of which are essential if you want your business to not only survive but thrive.

Interested in knowing more? Here we look at the benefits of AI and ML in the business world as well as the perceived challenges.

Customer service

We’ve probably all communicated with a chatbot online when searching our favourite store’s website. In fact, many might not even realise that when you use the chat box function, you’re not actually speaking to a human. This is one of the best examples of how technology can be used to help a business as it offers 24/7 customer support without breaks or vacations, and it’s likely to save money over time too. Even better, these chat boxes provide instant responses to customers, whatever time of the day, meaning customers are better served and we know that is crucial for customer retention and loyalty. That’s not to say there isn’t a place for human customer service agents, instead, your human team can be deployed to other areas of the business and can tackle more complex issues.

Administration

Data entry, accounts, general admin – these are all essential tasks for business owners to complete but it’s not always easy to find the time to dedicate to them. That’s where AI and ML come in. In fact, AI can automate data entry making it faster and error-free. It can even take care of administrative tasks, report generation, and appointment scheduling meaning you and your team can focus on business-critical tasks. With more time freed up, you’ll likely be able to respond quicker around the business and can put more time into your overall strategy.

Decision-making

Another benefit of AI is that it provides deeper insights and can analyse large amounts of data much quicker than a human could. This makes it even easier to predict market demand, understand specific customer preferences and optimise resource allocation.

The challenges in implementing AI

Despite the benefits of AI and ML, we can’t ignore the challenges surrounding it. This includes the difficulties in managing vast data storage, recruiting skilled AI professionals, and not to mention the rapid changes in the AI landscape. Indeed, implementing AI isn’t a one-stop approach. Instead, companies need to continuously innovate to ensure they can keep pace with competitors.

To Know More, Read Full Article @ https://ai-techpark.com/transforming-smes-for-success/

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In the ever-evolving world of retail, the holiday season presents unique challenges and opportunities for retailers. As consumer exertion surges, retailers have to be interactive with their customers, both online and in-store. To meet such demands effectively, embracing interactive and unified technology solutions is a strategic imperative for retailers to meet customers’ expectations and generate more sales. This article delves into the crucial aspects of interactive and unified technology in holiday customer service for retailers.

Proactive Message

Proactive order updates, delivery notifications, and personalized recommendations can be sent to customers via SMS, online messaging apps, or push notifications to keep them in the loop. This proactive approach builds trust and reduces unnecessary interactions, freeing up human agents for more complex issues.

Connect the Dots for a Seamless Journey for Unified Technology

Implementing a unified solution in retail streamlines operations enhances the customer experience, and optimizes resource utilization effectively. This section will delve into the practical steps for seamlessly integrating unified technology this holiday season:

Omnichannel Integration

Embracing an omnichannel integration strategy ensures a consistent customer experience across mobile applications, websites, and physical stores. A unified interface allows customers to seamlessly transition between channels.

Feedback Mechanism

Establishing a feedback mechanism to gather insight from customers helps in observing and experimenting with a unified solution to further refine it. With an adaptive approach based on the real world, this feedback is important for continuous improvement.

After learning about the types of interactive and unified technology solutions retailers can implement in their businesses, let’s further dive into how these technologies will help retailers this holiday season.

As retailers gear up for the holiday rush, embracing interactive customer support platforms and unified data management can change the customer service landscape. Investing in these solutions will ease the holiday rush and build long-lasting customer loyalty. So, as the holiday season approaches, these potential technologies will make your customers happy and orchestrate better sales and higher revenue.

To Know More, Read Full Article @ https://ai-techpark.com/interactive-and-unified-in-technology/

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Artificial intelligence (AI) has revolutionized data management, empowering organizations to leverage data for informed decision-making.This article explores the transformative impact of AI in data management, presenting three key ways it enhances insights.

First, how AI automates critical processes, optimizing workflows and resource allocation. Second, how AI algorithms improve data quality by detecting and rectifying errors, ensuring reliable insights. Last, how AI enables businesses to make informed decisions by uncovering patterns and making accurate predictions.

Embracing AI in data management provides a competitive advantage, driving sophisticated decision-making and valuable insights across industries. This article will highlight the transformative potential of AI in data management, informing data decision-makers why it is essential to seize this opportunity for growth and success.

About the writer: With more than 20 years of experience in software engineering, Jay Mishra is an expert in product vision and development. Jay is the Chief Operating Officer for Astera Software, where he focuses on product development and strategic planning. Jay holds a Master of Science degree in Computer Science from Virginia Tech and a Bachelor of Science in Mathematics and Computing from the Indian Institute of Technology.

Data: it is the backbone of businesses, enabling informed decision-making, enhanced customer service, and innovation. However, effectively managing data presents challenges, from collection to storage and analysis.

Integrating unstructured data is a challenging task due to its diverse formats and lack of structure. Managing this type of data has historically required extensive manual labor and complex systems to ensure the data is properly extracted. Even with a team of experts, there is still a risk of human error, from missing fields to duplications and inconsistencies.

The rise of artificial intelligence (AI) is revolutionizing data management practices, ushering in a new era of efficiency and efficacy. Large language models such as ChatGPT, Bing, and Google Bard are transforming both the speed at which we can process data, and the way we can use and understand that data.

Just as the advent of Excel revolutionized data processing and analysis, AI represents a new frontier in data management capabilities. While Excel brought the power of spreadsheets to the masses, large language models harness the capabilities of advanced language models to process and analyze data in a conversational manner. Unlike Excel’s structured and formula-based approach, AI’s natural language processing abilities enable users to interact with data in a more intuitive and conversational manner.

Using AI, businesses can now query, explore, and gain insights from their data using everyday language, eliminating the need for complex formulas and technical expertise. This opens up new possibilities for users of all backgrounds to effortlessly leverage data in their decision-making processes.

To Know More, Read Full Article @ https://ai-techpark.com/unlocking-the-power-of-ai/ 

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