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The Importance of Preparing Data for AI and ML

VANESSA WHITE | February 27, 2019 | 64 views

Machine Learning (ML) algorithms learn from data. It is critical that you feed them the right data for the problem you want to solve. Even if you have good data, you need to make sure that it is in a useful scale, format and even that meaningful features are included. Understand the key capabilities you need for collaborative, operational data preparation pipelines to serve the needs of both your data and business analysts. Some of these key functions include: Easily ingest and integrate data with more than 70 sources and formats.

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Is Progressive Web Apps the Way of the Future for Mobile?

Article | July 8, 2022

Progressive Web Apps (PWAs) enable cross-platform interoperability by giving users access to open web technologies. PWAs give your users an app-like experience that's tailored to their particular device. PWA development is a collection of best software development practices for making a web application behave like a mobile or desktop app. PWAs work similarly to mobile apps providing push notifications and a home screen icon. Progressive web applications, on the other hand, are more straightforward and faster than standard mobile apps, and they can be shared via a URL. According to Statista, there are around 3.5 billion smartphone users globally who utilize a variety of devices with various connection speeds and constantly changing conditions. Web App Vs. Progressive Web App The number of mobile users has expanded dramatically in recent years, necessitating the development of a better mobile web experience. Smartphones are utilized for a variety of purposes, such as reserving a cab or finding the nearest restaurant. Users expect a positive experience with their mobile devices in order to complete these tasks quickly. However, traditional websites are unable to give that experience for a variety of reasons, ranging from poor loading speeds to ambiguous user interfaces. Here's where web apps come in, which provide a better user experience regardless of the device or browser you're using. A typical web app is a website that can be accessed using a URL. Furthermore, these web apps contain several features that give them the appearance and feel of native apps, but they cannot be installed on any device. A progressive web app is the next step that can be installed on a device and appears and feels like a native app. You don't need to use a URL; just install a PWA on your device and run it like any other native app by clicking its icon on the home screen. Case Study Pinterest Pinterest built its new mobile web experience from the ground up as a PWA, with an eye toward worldwide expansion. However, due to poor mobile performance, the social network discovered that only 1% of its mobile users converted into sign-ups, logins, or app installs. Realizing that there was a big chance to boost conversion, they rebuilt the mobile web utilizing PWA technology, which resulted in a number of excellent outcomes: when compared to the prior mobile web, time spent is up 40%, user-generated ad income is up 44%, and core engagements are up 60%. Ali Baba Users of Alibaba's app were dissatisfied with their experience and refused to download or install the app. As a result, Alibaba had to make a progressive web application to make the experience much better for both first-time users and regular customers. As a result, seasoned users were re-engaged thanks to a significantly better experience for first-timers, push alerts, and home screen shortcuts. Alibaba could swiftly improve its re-engagement rate to match that of its native apps. To Sum It Up Developers may create the most excellent progressive apps using standard frameworks like React, Angular, Vue, Polymer, Ionic, and others, which have several advantages over native mobile apps and regular web pages in terms of functionality, user offline experience, and device space usage. Because of their superiority to native desktop and mobile apps in recent years, Progressive Web Programs have emerged as a wonderful alternative to those apps. PWAs take up less space on consumers' smartphones than native apps, encouraging people to install them. Because of caching capabilities, PWAs can work offline because some content is cached during the first visit to the app. Developing a great progressive web app necessitates a strong working relationship with a technical partner. Larger companies can also tap into the PWA industry by giving their users limited access to a PWA and then letting them pick how they want to continue. Overall, you should invest in PWA in 2022 since user experience is critical in this competitive market.

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FUTURE TECH

What Are The Best Programming Languages To Develop AI Solution

Article | July 26, 2022

As Artificial Intelligence becomes more popular, it’s essential to know the best programming languages AI uses. If you’re trying to code an AI software solution and don’t know which programming language(s) to use, it can hinder – even hurt – your development process. However, there are a lot of choices when it comes to programming languages you could use to develop an AI solution. So if you’re wondering what the best programming languages for AI are, you’re at the right place! Top 12 The Best Artificial Intelligence Programming Languages 1. Python Python development is one of the most popular programming languages globally and a top choice for AI developers. It’s easy to learn, runs on multiple platforms, and provides an interactive environment that allows you to quickly test ideas and make changes without waiting for a compile or deployment phase. Python development is also one of the fastest-growing languages in popularity and employment opportunities. You can use Python development in various AI applications, including natural language processing (NLP), machine learning, deep learning, and robotics. Python development has also been used in data science applications such as web scraping, web crawling, and scraping data from websites. 2. LISP LISP stands for List Processing Language or LISt Processor. It is a functional programming language that makes it easy to create functions that can manipulate lists of data items. John McCarthy created this language at MIT in 1958. It remains in use today because it is still an excellent vehicle for research in logic programming and because of its continued wide use in artificial intelligence applications such as natural language processing for semantic web applications. LISP is also great for creating neural networks because it can easily manipulate the network’s weights, which is usually the most challenging part of building a neural network. 3. R R is a free software environment for statistical computing and graphics that runs on multiple platforms, including Windows, Unix, macOS X, and Linux operating systems. Ross Ihaka created R and Robert Gentleman at the University of Auckland, New Zealand, in 1993, originally under the name “S.” R provides different analysis methods such as linear regression, generalized linear models, time series analysis, classification, and clustering. The main advantage of using R is that it allows users to develop complex algorithms without having to write complicated code or spend time debugging the code. Its popularity has increased significantly over time due to its ease of use and flexibility from simple linear regressions to multi-level modeling approaches. 4. C++ It is one of the most popular and widely used programming languages for developing AI solutions. It is a general-purpose language used to create software applications, operating systems, and other programs. Bjarne Stroustrup originally developed C++ to enhance C with object-oriented features. Its popularity has increased due to its ability to support multiple paradigms, including object-oriented programming (OOP), imperative and procedural programming techniques, generic programming, and others. 5. JavaScript Netscape Communications Corporation developed JavaScript in 1995, but the standardization of JavaScript only began in 1997 when Ecma International adopted it as ECMAScript. JavaScript is a programming language used by over 65% of developers to create interactive web pages. It is prevalent because you can run it on all modern browsers without installing plug-ins or additional software. You can use JavaScript to create web pages and applications on web browsers and mobile devices like smartphones and tablets. JavaScript also has an object-oriented structure, making it easy for programmers to build complex programs using multiple objects. 6. Java Java is one of the most popular programming languages in the world. As a platform, it has excellent support for AI development. You can use Java for developing machine learning algorithms, deep learning frameworks, and other tools. Many of the most popular libraries and frameworks are written in Java, including Hadoop and TensorFlow. Java is also very popular with enterprises because it has excellent performance, scalability, and portability across different operating systems and hardware platforms. 7. Haskell Haskell is an excellent choice for AI development because it allows for the use of a functional programming paradigm. It means that it will enable you to write your code in a way that focuses on composing functions together instead of focusing on variables and data structures. While this may not seem like a big deal, it makes it easier to reason about your code and make changes without introducing errors. Haskell also has strong type inference capabilities, which allow you to focus on what your program does rather than how it does it. It also makes writing tests and ensuring that your code works as expected without manually testing every possible case. 8. Julia Julia is a high-level, high-performance programming language that makes coding fast and efficient. It’s great for AI development because it’s flexible and easy to learn. Julia combines the speed of C with the usability of Python, making it ideal for numerical computing. Julia is a multi-paradigm programming language that allows you to write code in numerous styles – from functional to imperative, object-oriented to metaprogramming – all within the same program. You can hire an AI developer to take advantage of the best tools for each task instead of forcing everyone down a single path. 9. Prolog One of the most popular programming languages for developing AI solutions is Prolog. It was developed in 1972 and used for decades as a powerful logic programming language. Prolog uses an underlying theory called predicate logic based on facts, rules, and inference. Prolog became popular due to its ability to represent knowledge in a form that can be queried and reasoned about. It makes it ideal for solving problems that require reasoning about the world. Another reason Prolog is so famous for developing AI solutions is because it allows you to hire AI developers to combine logic programming with declarative programming through pattern matching and unification. 10. Scala Scala is a general-purpose programming language that runs on the Java virtual machine. It can be used in distributed and parallel systems, developing scalable software applications. Scala is easy to learn because it integrates object-oriented languages with functional programming features. It was developed by Martin Odersky in 2001 at École Polytechnique Fédérale de Lausanne in Switzerland as an academic research project. Many companies have used Scala to develop AI applications. It has an advantage over other programming languages because it allows to hire AI developers to get the best of both worlds, i.e., object-oriented and functional programming paradigms. Scala is statically typed and uses JVM for execution. You can use Scala for building web applications and big data applications. 11. RUST The Rust programming language is one of the most popular languages for developing AI solutions. It was developed by Mozilla and was released in 2010. The main goal of Rust is to provide a safe, fast, productive, and memory-safe language. Performance is one of the main features of the rust programming language because it can work on a low level with C/C++ and other systems programming languages. Rust is also suitable for machine learning because you can use it to write efficient code without sacrificing safety or performance. 12. Wolfram Wolfram is a programming language and environment for technical computing, data science, and machine learning. Students, teachers, researchers, and commercial developers worldwide develop applications that range from technical and scientific to financial analysis, music generation, and art creation. Wolfram is a great place to start if you’re new to programming because it has a clean syntax that makes it easier to understand than other languages. It’s also inherently visual – you can build your code by dragging blocks together on a canvas. So you don’t need to spend time learning how to write code from scratch before getting started.

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SOFTWARE

Web 3.0: New Horizon of Internet

Article | July 13, 2022

Web 3.0, or as it is commonly known as Web3, is the future avatar of the world of the internet and it is based on decentralization. The present-day internet, or Web 2.0 as it should correctly be referred to, has contributed a lot more to transforming the way we live than any other tool in the universe. Web2 has been a key part of building the digital world we live in today, from Snapchat and Instagram filters to using Augmented Reality (AR) to catch Pokémon. Web3 and Metaverse are the most popular buzzwords today. With the decentralized network, Web 3.0 means that instead of having a few large companies control all the data, users will have equal access to control their data. Web3 also promises to enhance data and network privacy. What does Web 3.0 Mean for Businesses? Web 3.0 presents enormous opportunities for businesses. Let’s explore some of the ways in which Web3 will benefit from this new technology. Enhance Transparency and Trust Web 3.0 technology may help organizations and their consumers boost transparency and trust. Blockchain technology, for instance, can contribute to the creation of a tamper-proof record of transactions. This would help businesses increase customer trust by giving customers a clear picture of how they do business. Increased Security Presently, in Web 2.0, all of your data is saved in one spot in a centralized system. As a result, it is prone to exploitation. However, nothing is more crucial to a company than data security. Web 3.0 technologies decentralizes your data and assists in increasing its security. Deeper Customer Insights Web 3.0 can also help organizations acquire customer insights. How? Web 3.0 brings in data anonymization that allows businesses acquire customer data without fetching their personal data. It also helps businesses scale consumer data at large without any compromise on privacy. The data then gathered through customer insights can be utilized to enhance products and services. Finer Data Searchability Businesses can also deploy Web 3.0 technology to improve the searchability of their data. Using technologies for the semantic web can help make a data web that is easy for machines to search. This would make it easy for companies to get the information they need quickly and without wasting money or time on manual data searches. Better User Experience (UX) By offering a more customized web, Web 3.0 technologies can assist in enhancing the user experience. Artificial intelligence and machine learning algorithms can assist in giving each user a personalized experience that is suited to their specific requirements. As a result, consumer satisfaction and loyalty will rise. Web 3.0 Possible Business Applications Some of the most common possible areas where Web3 will definitely have an effect are: Social Media Web 3.0 transforms how app developers create social media apps. It returns ownership of data from platforms to end-users, making story-spinning and data exploitation impossible, as in the Facebook Cambridge Analytics Scandal. Currency Exchange Service Centralization fails in money exchange. Mt. Gox's $460 million bitcoin hack is a failure. Decentralized exchanges prevent hacker breeding grounds. Web 3.0 will see decentralized exchanges gain popularity for smooth user trades without hackers or lack of transparency. Messaging Platforms Messaging has always played an essential role in our lives. At work, Slack and Telegram replace Facebook Messenger and WhatsApp. Unsafe message transmission and centralized solutions make messaging systems exploitable. Web 3.0 messaging applications like ySign, Obsidian, e-Chat, etc., leverage Blockchain to protect users' privacy and security. Summing-up The Internet's evolution has been substantial, and this trend will undoubtedly continue. Web 3.0 will revolutionize the way we engage with the digital world, and the transition will affect more than just individuals. This will lead to more honest and transparent use of customer data, from tailored search results to cross-platform development tools and 3D graphics. A much more immersive and engaging web is on the way. The new Internet will be around very soon! Let's welcome Web 3.0 with open arms!

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SOFTWARE

Natural Language Processing: An Advanced Implementation of AI

Article | June 1, 2022

Natural Language Processing, also known as computational linguistics or NLP, is a branch of Artificial Intelligence (AI), Machine Learning (ML), and linguistics. It is a subfield of AI that enables computers or machines to understand, manipulate, and interpret human language. Simply put, natural language is the natural method by which humans communicate with one another. We have now trained computers to interpret natural language. Communicating with computers has become simpler with voice queries such as "Alexa, what's the news today?" or "Ok Google, play my favorite songs." Similarly, when you ask Siri, Apple's voice assistant, "What is the cheapest flight to New York later today?" It instantly searches airline and travel websites for flights from the user's location to New York. It also compares the prices and lists the one with the lowest fare first. So, even without specifying a date or the "lowest fare", Siri understands the inquiry and returns accurate results. This is the result of NLP in action. Natural Language Processing: Business Applications Natural language processing has a variety of applications, some of them are listed below. Summarize text blocks to extract the most relevant and core concepts while excluding unnecessary information. Develop a chatbot that makes use of Point-of-Speech tagging to enhance customer support. Chatbots are AI systems that use NLP to engage with people through text or voice. Determine the type of extracted entity, such as a person, location, or organization. Sentiment Analysis can be used to recognize the sentiment or emotions of a text string, ranging from highly negative to neutral to very positive. HR teams can utilize NLP-based solutions to scan resumes based on keyword synonyms and swiftly shortlist candidates from a pile of resumes. Extracting Text data from the data storage allows in extracting specific information from text. Text can be broken down into tokens, or words can be reduced to their root or stem. Topic categorization helps users organize unstructured text. It's a great way for businesses to obtain insights from customer feedback. How Can Businesses Prepare for the NLP-Powered Future? NLP has evolved tremendously, and has benefited both companies and consumers. NLP technologies are assisting businesses to better understand how consumers perceive them through channels such as emails, product reviews, social media postings, surveys, and more. AI technologies can be used not just to analyze online interactions and how people speak about companies but also to automate tedious and time-consuming operations, enhance productivity, and free up staff to concentrate on more meaningful duties. When it comes to NLP the sky is the limit. As NLP technology is becoming more prevalent and greater advancements in ability are explored, the future will witness enormous shifts. Here are some of the ways in which businesses can prepare for the future of NLP. Analyze your company's text data assets and evaluate how the most recent techniques can be used to add value. Understand how you can use AI-powered language technology to make wiser decisions or rearrange your skilled labor. Start implementing new language-based AI tools for a range of jobs in order to better understand their potential. Prepare now to capitalize on transformative AI and to make sure that advanced AI contributes to society fairly. Closing Note Thanks to natural language processing technology, conversational commands and everything related to conversational AI in businesses have become faster and better. Natural language processing helps large businesses make flexible choices by revealing consumer moods and market movements. Smart companies now make decisions based not only on data but also on the intelligence derived from NLP-powered system data.

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The Evolution of Quantum Computing and What its Future Beholds

Article | July 8, 2022

Progressive Web Apps (PWAs) enable cross-platform interoperability by giving users access to open web technologies. PWAs give your users an app-like experience that's tailored to their particular device. PWA development is a collection of best software development practices for making a web application behave like a mobile or desktop app. PWAs work similarly to mobile apps providing push notifications and a home screen icon. Progressive web applications, on the other hand, are more straightforward and faster than standard mobile apps, and they can be shared via a URL. According to Statista, there are around 3.5 billion smartphone users globally who utilize a variety of devices with various connection speeds and constantly changing conditions. Web App Vs. Progressive Web App The number of mobile users has expanded dramatically in recent years, necessitating the development of a better mobile web experience. Smartphones are utilized for a variety of purposes, such as reserving a cab or finding the nearest restaurant. Users expect a positive experience with their mobile devices in order to complete these tasks quickly. However, traditional websites are unable to give that experience for a variety of reasons, ranging from poor loading speeds to ambiguous user interfaces. Here's where web apps come in, which provide a better user experience regardless of the device or browser you're using. A typical web app is a website that can be accessed using a URL. Furthermore, these web apps contain several features that give them the appearance and feel of native apps, but they cannot be installed on any device. A progressive web app is the next step that can be installed on a device and appears and feels like a native app. You don't need to use a URL; just install a PWA on your device and run it like any other native app by clicking its icon on the home screen. Case Study Pinterest Pinterest built its new mobile web experience from the ground up as a PWA, with an eye toward worldwide expansion. However, due to poor mobile performance, the social network discovered that only 1% of its mobile users converted into sign-ups, logins, or app installs. Realizing that there was a big chance to boost conversion, they rebuilt the mobile web utilizing PWA technology, which resulted in a number of excellent outcomes: when compared to the prior mobile web, time spent is up 40%, user-generated ad income is up 44%, and core engagements are up 60%. Ali Baba Users of Alibaba's app were dissatisfied with their experience and refused to download or install the app. As a result, Alibaba had to make a progressive web application to make the experience much better for both first-time users and regular customers. As a result, seasoned users were re-engaged thanks to a significantly better experience for first-timers, push alerts, and home screen shortcuts. Alibaba could swiftly improve its re-engagement rate to match that of its native apps. To Sum It Up Developers may create the most excellent progressive apps using standard frameworks like React, Angular, Vue, Polymer, Ionic, and others, which have several advantages over native mobile apps and regular web pages in terms of functionality, user offline experience, and device space usage. Because of their superiority to native desktop and mobile apps in recent years, Progressive Web Programs have emerged as a wonderful alternative to those apps. PWAs take up less space on consumers' smartphones than native apps, encouraging people to install them. Because of caching capabilities, PWAs can work offline because some content is cached during the first visit to the app. Developing a great progressive web app necessitates a strong working relationship with a technical partner. Larger companies can also tap into the PWA industry by giving their users limited access to a PWA and then letting them pick how they want to continue. Overall, you should invest in PWA in 2022 since user experience is critical in this competitive market.

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FUTURE TECH

Analyzing the Potential of Digital Business Models

Article | July 26, 2022

As Artificial Intelligence becomes more popular, it’s essential to know the best programming languages AI uses. If you’re trying to code an AI software solution and don’t know which programming language(s) to use, it can hinder – even hurt – your development process. However, there are a lot of choices when it comes to programming languages you could use to develop an AI solution. So if you’re wondering what the best programming languages for AI are, you’re at the right place! Top 12 The Best Artificial Intelligence Programming Languages 1. Python Python development is one of the most popular programming languages globally and a top choice for AI developers. It’s easy to learn, runs on multiple platforms, and provides an interactive environment that allows you to quickly test ideas and make changes without waiting for a compile or deployment phase. Python development is also one of the fastest-growing languages in popularity and employment opportunities. You can use Python development in various AI applications, including natural language processing (NLP), machine learning, deep learning, and robotics. Python development has also been used in data science applications such as web scraping, web crawling, and scraping data from websites. 2. LISP LISP stands for List Processing Language or LISt Processor. It is a functional programming language that makes it easy to create functions that can manipulate lists of data items. John McCarthy created this language at MIT in 1958. It remains in use today because it is still an excellent vehicle for research in logic programming and because of its continued wide use in artificial intelligence applications such as natural language processing for semantic web applications. LISP is also great for creating neural networks because it can easily manipulate the network’s weights, which is usually the most challenging part of building a neural network. 3. R R is a free software environment for statistical computing and graphics that runs on multiple platforms, including Windows, Unix, macOS X, and Linux operating systems. Ross Ihaka created R and Robert Gentleman at the University of Auckland, New Zealand, in 1993, originally under the name “S.” R provides different analysis methods such as linear regression, generalized linear models, time series analysis, classification, and clustering. The main advantage of using R is that it allows users to develop complex algorithms without having to write complicated code or spend time debugging the code. Its popularity has increased significantly over time due to its ease of use and flexibility from simple linear regressions to multi-level modeling approaches. 4. C++ It is one of the most popular and widely used programming languages for developing AI solutions. It is a general-purpose language used to create software applications, operating systems, and other programs. Bjarne Stroustrup originally developed C++ to enhance C with object-oriented features. Its popularity has increased due to its ability to support multiple paradigms, including object-oriented programming (OOP), imperative and procedural programming techniques, generic programming, and others. 5. JavaScript Netscape Communications Corporation developed JavaScript in 1995, but the standardization of JavaScript only began in 1997 when Ecma International adopted it as ECMAScript. JavaScript is a programming language used by over 65% of developers to create interactive web pages. It is prevalent because you can run it on all modern browsers without installing plug-ins or additional software. You can use JavaScript to create web pages and applications on web browsers and mobile devices like smartphones and tablets. JavaScript also has an object-oriented structure, making it easy for programmers to build complex programs using multiple objects. 6. Java Java is one of the most popular programming languages in the world. As a platform, it has excellent support for AI development. You can use Java for developing machine learning algorithms, deep learning frameworks, and other tools. Many of the most popular libraries and frameworks are written in Java, including Hadoop and TensorFlow. Java is also very popular with enterprises because it has excellent performance, scalability, and portability across different operating systems and hardware platforms. 7. Haskell Haskell is an excellent choice for AI development because it allows for the use of a functional programming paradigm. It means that it will enable you to write your code in a way that focuses on composing functions together instead of focusing on variables and data structures. While this may not seem like a big deal, it makes it easier to reason about your code and make changes without introducing errors. Haskell also has strong type inference capabilities, which allow you to focus on what your program does rather than how it does it. It also makes writing tests and ensuring that your code works as expected without manually testing every possible case. 8. Julia Julia is a high-level, high-performance programming language that makes coding fast and efficient. It’s great for AI development because it’s flexible and easy to learn. Julia combines the speed of C with the usability of Python, making it ideal for numerical computing. Julia is a multi-paradigm programming language that allows you to write code in numerous styles – from functional to imperative, object-oriented to metaprogramming – all within the same program. You can hire an AI developer to take advantage of the best tools for each task instead of forcing everyone down a single path. 9. Prolog One of the most popular programming languages for developing AI solutions is Prolog. It was developed in 1972 and used for decades as a powerful logic programming language. Prolog uses an underlying theory called predicate logic based on facts, rules, and inference. Prolog became popular due to its ability to represent knowledge in a form that can be queried and reasoned about. It makes it ideal for solving problems that require reasoning about the world. Another reason Prolog is so famous for developing AI solutions is because it allows you to hire AI developers to combine logic programming with declarative programming through pattern matching and unification. 10. Scala Scala is a general-purpose programming language that runs on the Java virtual machine. It can be used in distributed and parallel systems, developing scalable software applications. Scala is easy to learn because it integrates object-oriented languages with functional programming features. It was developed by Martin Odersky in 2001 at École Polytechnique Fédérale de Lausanne in Switzerland as an academic research project. Many companies have used Scala to develop AI applications. It has an advantage over other programming languages because it allows to hire AI developers to get the best of both worlds, i.e., object-oriented and functional programming paradigms. Scala is statically typed and uses JVM for execution. You can use Scala for building web applications and big data applications. 11. RUST The Rust programming language is one of the most popular languages for developing AI solutions. It was developed by Mozilla and was released in 2010. The main goal of Rust is to provide a safe, fast, productive, and memory-safe language. Performance is one of the main features of the rust programming language because it can work on a low level with C/C++ and other systems programming languages. Rust is also suitable for machine learning because you can use it to write efficient code without sacrificing safety or performance. 12. Wolfram Wolfram is a programming language and environment for technical computing, data science, and machine learning. Students, teachers, researchers, and commercial developers worldwide develop applications that range from technical and scientific to financial analysis, music generation, and art creation. Wolfram is a great place to start if you’re new to programming because it has a clean syntax that makes it easier to understand than other languages. It’s also inherently visual – you can build your code by dragging blocks together on a canvas. So you don’t need to spend time learning how to write code from scratch before getting started.

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SOFTWARE

The Impact of VR and AR on the Automotive Industry

Article | July 13, 2022

Web 3.0, or as it is commonly known as Web3, is the future avatar of the world of the internet and it is based on decentralization. The present-day internet, or Web 2.0 as it should correctly be referred to, has contributed a lot more to transforming the way we live than any other tool in the universe. Web2 has been a key part of building the digital world we live in today, from Snapchat and Instagram filters to using Augmented Reality (AR) to catch Pokémon. Web3 and Metaverse are the most popular buzzwords today. With the decentralized network, Web 3.0 means that instead of having a few large companies control all the data, users will have equal access to control their data. Web3 also promises to enhance data and network privacy. What does Web 3.0 Mean for Businesses? Web 3.0 presents enormous opportunities for businesses. Let’s explore some of the ways in which Web3 will benefit from this new technology. Enhance Transparency and Trust Web 3.0 technology may help organizations and their consumers boost transparency and trust. Blockchain technology, for instance, can contribute to the creation of a tamper-proof record of transactions. This would help businesses increase customer trust by giving customers a clear picture of how they do business. Increased Security Presently, in Web 2.0, all of your data is saved in one spot in a centralized system. As a result, it is prone to exploitation. However, nothing is more crucial to a company than data security. Web 3.0 technologies decentralizes your data and assists in increasing its security. Deeper Customer Insights Web 3.0 can also help organizations acquire customer insights. How? Web 3.0 brings in data anonymization that allows businesses acquire customer data without fetching their personal data. It also helps businesses scale consumer data at large without any compromise on privacy. The data then gathered through customer insights can be utilized to enhance products and services. Finer Data Searchability Businesses can also deploy Web 3.0 technology to improve the searchability of their data. Using technologies for the semantic web can help make a data web that is easy for machines to search. This would make it easy for companies to get the information they need quickly and without wasting money or time on manual data searches. Better User Experience (UX) By offering a more customized web, Web 3.0 technologies can assist in enhancing the user experience. Artificial intelligence and machine learning algorithms can assist in giving each user a personalized experience that is suited to their specific requirements. As a result, consumer satisfaction and loyalty will rise. Web 3.0 Possible Business Applications Some of the most common possible areas where Web3 will definitely have an effect are: Social Media Web 3.0 transforms how app developers create social media apps. It returns ownership of data from platforms to end-users, making story-spinning and data exploitation impossible, as in the Facebook Cambridge Analytics Scandal. Currency Exchange Service Centralization fails in money exchange. Mt. Gox's $460 million bitcoin hack is a failure. Decentralized exchanges prevent hacker breeding grounds. Web 3.0 will see decentralized exchanges gain popularity for smooth user trades without hackers or lack of transparency. Messaging Platforms Messaging has always played an essential role in our lives. At work, Slack and Telegram replace Facebook Messenger and WhatsApp. Unsafe message transmission and centralized solutions make messaging systems exploitable. Web 3.0 messaging applications like ySign, Obsidian, e-Chat, etc., leverage Blockchain to protect users' privacy and security. Summing-up The Internet's evolution has been substantial, and this trend will undoubtedly continue. Web 3.0 will revolutionize the way we engage with the digital world, and the transition will affect more than just individuals. This will lead to more honest and transparent use of customer data, from tailored search results to cross-platform development tools and 3D graphics. A much more immersive and engaging web is on the way. The new Internet will be around very soon! Let's welcome Web 3.0 with open arms!

Read More
SOFTWARE

Natural Language Processing: An Advanced Implementation of AI

Article | June 1, 2022

Natural Language Processing, also known as computational linguistics or NLP, is a branch of Artificial Intelligence (AI), Machine Learning (ML), and linguistics. It is a subfield of AI that enables computers or machines to understand, manipulate, and interpret human language. Simply put, natural language is the natural method by which humans communicate with one another. We have now trained computers to interpret natural language. Communicating with computers has become simpler with voice queries such as "Alexa, what's the news today?" or "Ok Google, play my favorite songs." Similarly, when you ask Siri, Apple's voice assistant, "What is the cheapest flight to New York later today?" It instantly searches airline and travel websites for flights from the user's location to New York. It also compares the prices and lists the one with the lowest fare first. So, even without specifying a date or the "lowest fare", Siri understands the inquiry and returns accurate results. This is the result of NLP in action. Natural Language Processing: Business Applications Natural language processing has a variety of applications, some of them are listed below. Summarize text blocks to extract the most relevant and core concepts while excluding unnecessary information. Develop a chatbot that makes use of Point-of-Speech tagging to enhance customer support. Chatbots are AI systems that use NLP to engage with people through text or voice. Determine the type of extracted entity, such as a person, location, or organization. Sentiment Analysis can be used to recognize the sentiment or emotions of a text string, ranging from highly negative to neutral to very positive. HR teams can utilize NLP-based solutions to scan resumes based on keyword synonyms and swiftly shortlist candidates from a pile of resumes. Extracting Text data from the data storage allows in extracting specific information from text. Text can be broken down into tokens, or words can be reduced to their root or stem. Topic categorization helps users organize unstructured text. It's a great way for businesses to obtain insights from customer feedback. How Can Businesses Prepare for the NLP-Powered Future? NLP has evolved tremendously, and has benefited both companies and consumers. NLP technologies are assisting businesses to better understand how consumers perceive them through channels such as emails, product reviews, social media postings, surveys, and more. AI technologies can be used not just to analyze online interactions and how people speak about companies but also to automate tedious and time-consuming operations, enhance productivity, and free up staff to concentrate on more meaningful duties. When it comes to NLP the sky is the limit. As NLP technology is becoming more prevalent and greater advancements in ability are explored, the future will witness enormous shifts. Here are some of the ways in which businesses can prepare for the future of NLP. Analyze your company's text data assets and evaluate how the most recent techniques can be used to add value. Understand how you can use AI-powered language technology to make wiser decisions or rearrange your skilled labor. Start implementing new language-based AI tools for a range of jobs in order to better understand their potential. Prepare now to capitalize on transformative AI and to make sure that advanced AI contributes to society fairly. Closing Note Thanks to natural language processing technology, conversational commands and everything related to conversational AI in businesses have become faster and better. Natural language processing helps large businesses make flexible choices by revealing consumer moods and market movements. Smart companies now make decisions based not only on data but also on the intelligence derived from NLP-powered system data.

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FUTURE TECH

Vendr Launches 2.0, The Most Complete SaaS Buying Platform on The Market

Vendr | August 10, 2022

Vendr, the world’s first SaaS buying platform, today announced the launch of Vendr 2.0, the most complete SaaS buying platform on the market. SaaS is a top-three line item expense, but most companies aren’t getting the appropriate return on their software investment. Vendr 2.0 harnesses Vendr’s SaaS purchasing and SaaS management products, combining the power of seasoned negotiators armed with insights from over 13,000 deals alongside robust software featuring an integrated system of record. Now, enterprise customers will be equipped with an unprecedented level of visibility into which software their teams are buying and using — in one central location. This enables leaders to reduce overspend and eliminate duplicative products. Most importantly, it unlocks insights that lead to better software choices and faster procurement at lower prices. The launch comes on the heels of the company’s recent ​​$150MM Series B, co-led by return investor Craft Ventures and new investor SoftBank Vision Fund 2––which brought the company into Unicorn status––and its acquisition of SaaS management company Blissfully earlier this year. “The software purchasing process is broken and becoming all the more cumbersome as companies everywhere work to cut costs, as they seek to do more with less. “The introduction of Vendr 2.0 enables organizations to manage their second-highest expense––software––more effectively than ever before, while reducing the difficulties surrounding the process. Vendr 2.0 aims to be the most complete, no-brainer, SaaS buying platform on the market –– and one that pays for itself.” Ryan Neu, Vendr CEO and co-founder The standard buying process historically wastes time and resources for both software vendors and customers. Vendr enables businesses to maximize the return on their SaaS investments through cost savings and more efficient spend, improving stack visibility across the organization. Composed of the best industry data of more than 2,000 SaaS suppliers, Vendr 2.0 is facilitating critical transformation in how organizations purchase and manage software. Tapping Into Transparency Software buying is a perpetual process and it no longer makes sense to have buying and supplier lifecycle management exist in disparate places. By bringing everything into one place, companies layer the benefits of an expert service team and deep SaaS insights into an integrated system of record that offers unparalleled visibility into their stack. Using Vendr, customers can take a proactive approach to their SaaS spend, equipping their teams with the best software while saving money. Buyer <-> supplier: Vendr offers insights and negotiation support to help buyers and sellers quickly evaluate whether a deal is fair for both sides, ensuring that the process continues moving along internally once it comes time to buy. Buyer <-> procurement function: Vendr provides visibility into internal approval workflows and offers fast-tracked ways to request purchases, leading to smoother relationships between buyers and their company procurement functions. Finance/procurement <-> department heads: With better visibility and faster purchase cycles, stakeholders can easily see the value-add of finance and procurement, ensuring compliance and keeping a handle on costs, leading to better business outcomes for all. This new platform builds upon the competitive advantages that Vendr has in the market as the category creator with the deepest source of supplier insight––based on thousands of deals––as well as the most seasoned negotiators in the industry. Vendr has processed over $1.5B in customer software spend and delivered over $240M in software savings to its customers. To see how much you could be saving on your annual software expense, get in touch here. About Vendr Vendr is changing how companies find, buy and manage SaaS. The first of its kind, Vendr's SaaS buying platform offers both a product and people-powered service to enable the world's fastest-growing companies to purchase software quickly and with guaranteed savings. Today, Vendr has facilitated over $1.5B+ in SaaS purchases across 2,500+ suppliers for Finance and Procurement teams at HubSpot, Brex, Canva, Reddit, Toast, and more. Headquartered in Boston with a second location in Charleston, Vendr was founded in 2019 by Ryan Neu and co-founders Ariel Diaz and Aaron White, who joined the team through the acquisition of Blissfully in 2022. The company has over 250 employees globally

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SOFTWARE

New Relic Brings Error Tracking into Atlassian Open DevOps Solution

New Relic | August 10, 2022

New Relic , the observability company, today announced it has joined the Atlassian Platform Partner Program as part of the Atlassian Open DevOps solution that integrates Jira Software with popular DevOps tools. New Relic has integrated errors inbox with Jira Software to empower developers to easily access and set up full stack error tracking and software performance monitoring from inside Jira Software, Atlassian’s issue and project management tool. With this integration, developers can create Jira Software issues directly within errors inbox, the New Relic platform functionality for error tracking. This announcement coincides with the launch of the Jira Software toolchain page, which helps developer teams to discover and install DevOps tools to improve DevOps practices across their software development lifecycle. “As applications grow more complex, developers need a system in place to proactively fix errors before the customer experience is impacted,” said Peter Pezaris, SVP, Strategy and User Experience at New Relic. “Errors inbox for Jira Software, which builds on the strong history between New Relic and Atlassian, makes developers’ lives easier by allowing them to get to the root cause faster with full error details — including stack traces — and alerts whenever a critical, customer-impacting error arises. Ticketing is made easier, too, as teams can instantly create Jira Software issues with all the right information, without leaving their error management workflow.” Key benefits and capabilities of the New Relic and Jira Software integration include: Track, triage, and resolve errors in one place: Errors are grouped and displayed on a single screen for visibility and easy triaging. Tackle errors across the full application stack with APM, RUM, Mobile, and Serverless (Lambda Functions) data tracked. Resolve errors before impacting customers: Proactively review and triage errors before they affect customers. Get to the root cause faster with full error details, including stack traces and logs in context, provided in the error inbox. Collaborate across teams: Squash bugs as a team with shared error visibility, shared comments, and an integration with Slack. Create Jira Software issues with a click: With the new integration, set up templates and quickly file Jira ​​Software issues containing error details, associated issues, and direct links to the stack trace and entities in New Relic for easy debugging. “Atlassian and New Relic share a vision to improve the developer experience by meeting users where they are and allowing them to use the tools they know and love. “We are excited to include New Relic errors inbox as an app in the Jira Software toolchain page, which makes it easier for millions of users to discover and connect DevOps apps used throughout the software development lifecycle to fill gaps in the toolchain as their DevOps practices evolve.” Bryant Lee, VP of Partnerships and Developer Experience at Atlassian “We have been really impressed with how New Relic errors inbox offers a single place to track all the errors for the entire stack," said Mudit Mehta, Software Engineer II at Postman. "Errors inbox helps developers save time instead of looking and jumping through multiple tools for cloud-based or external error tracking. With the integration for Jira Software, I can quickly view an error and notify the right team members by filing a templated Jira Software issue in seconds without even leaving the New Relic platform.” The Jira Software toolchain page is the latest collaboration between New Relic and Atlassian. The integration builds on the recent launch of the Bitbucket quickstart in New Relic Instant Observability, which gives engineers visibility into the health and performance of their Bitbucket pipelines to continuously improve and optimize their deployments. Developers can also connect Jira Software to New Relic alerts to help the right teams get the right information in the software development life cycle. Errors inbox for Jira Software is available for free to all New Relic full platform users and Jira Cloud users. For more information, visit www.newrelic.com. Additional integrations for Atlassian’s Connect applications with errors inbox and other capabilities will be available later this year. About New Relic As a leader in observability, New Relic empowers engineers with a data-driven approach to planning, building, deploying, and running great software. New Relic delivers the only unified data platform that empowers engineers to get all telemetry—metrics, events, logs, and traces—paired with powerful full stack analysis tools to help engineers do their best work with data, not opinions. Delivered through the industry’s first usage-based consumption pricing that’s intuitive and predictable, New Relic gives engineers more value for the money by helping improve planning cycle times, change failure rates, release frequency, and mean time to resolution. This helps the world’s leading brands including adidas Runtastic, American Red Cross, Australia Post, Banco Inter, Chegg, GoTo Group, Ryanair, Sainsbury’s, Signify Health, TopGolf, and World Fuel Services (WFS) improve uptime, reliability, and operational efficiency to deliver exceptional customer experiences that fuel innovation and growth.

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AI TECH

XSELL Technologies Announces Partnership with Five9 to Deliver Results that Matter

XSELL Technologies | August 09, 2022

XSELL Technologies, a leader in conversational AI for contact center agent optimization, announced that XSELL Agent Experience powered by VoiceStream is available on the Five9 CX Marketplace, empowering customers to amplify top performer outcomes across their contact centers. Leveraging the strength of Five9 cloud contact center solutions, the partnership makes it easy for businesses to integrate XSELL Agent Experience with the Five9 Intelligent Cloud Contact Center. Working together, Five9 and XSELL partnered to deliver real results to a healthcare customer, in the form of $6.9 million in annual incremental profit, an 11% increase in conversion rate and a 52% increase in appointments booked by agents. Read more in the just-published case study: “Health Insurance Provider Uses AI Conversion Maps to Drive Patient Acquisition, Engagement, and Retention with Care at Home.” “We are delighted to bring the power of XSELL Agent Experience to Five9 CX Marketplace to support organizations in their pursuit of a better customer experience while delivering results that matter.” Matt Coughlin, Founder and CEO, XSELL Technologies The Five9 platform facilitates billions of call minutes annually and provides digital engagement, analytics, workflow automation, workforce optimization, and practical AI to create more human customer experiences, engage and empower contact center agents, and deliver tangible business results. XSELL’s AI-powered technology takes a data-driven approach to consistently delivering top performer outcomes by identifying and replicating specialized skill sets, with precision and at scale, across every agent, enterprise-wide. With XSELL Agent Experience, businesses can access AI-generated guidance to improve their customer and agent experience in real-time across the enterprise, driving tangible results like increased NPS scores, decreased Average Handle Time (AHT), and increasing Speed to Proficiency. “Five9 is committed to delivering AI solutions that improve the customer and agent experience, and we are excited to work with partners like XSELL who want to build on our VoiceStream platform to deliver additional innovation and use cases with that same goal in mind,” said Jake Butterbaugh, SVP Global Partner Sales, Five9. XSELL Technologies is sponsoring Five9 CX Summit, taking place Aug. 9-11 at the Aria Resort & Casino in Las Vegas, and will demonstrate XSELL Agent Experience in the CX Hub at the event. Five9 CX Summit is the #1 cloud contact center conference dedicated to making CX work for real life. Learn more about the event, including how to register, here. About XSELL Technologies XSELL Technologies was founded on the belief that the behaviors of the best contact center agents could be learned, replicated, and amplified to every agent in real-time to transform the way that businesses interact with their customers. Today, the XSELL team is partnering with Fortune 50 customers to drive quantifiable improvements in sales results, service metrics, agent engagement, and the overall customer experience.

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FUTURE TECH

Vendr Launches 2.0, The Most Complete SaaS Buying Platform on The Market

Vendr | August 10, 2022

Vendr, the world’s first SaaS buying platform, today announced the launch of Vendr 2.0, the most complete SaaS buying platform on the market. SaaS is a top-three line item expense, but most companies aren’t getting the appropriate return on their software investment. Vendr 2.0 harnesses Vendr’s SaaS purchasing and SaaS management products, combining the power of seasoned negotiators armed with insights from over 13,000 deals alongside robust software featuring an integrated system of record. Now, enterprise customers will be equipped with an unprecedented level of visibility into which software their teams are buying and using — in one central location. This enables leaders to reduce overspend and eliminate duplicative products. Most importantly, it unlocks insights that lead to better software choices and faster procurement at lower prices. The launch comes on the heels of the company’s recent ​​$150MM Series B, co-led by return investor Craft Ventures and new investor SoftBank Vision Fund 2––which brought the company into Unicorn status––and its acquisition of SaaS management company Blissfully earlier this year. “The software purchasing process is broken and becoming all the more cumbersome as companies everywhere work to cut costs, as they seek to do more with less. “The introduction of Vendr 2.0 enables organizations to manage their second-highest expense––software––more effectively than ever before, while reducing the difficulties surrounding the process. Vendr 2.0 aims to be the most complete, no-brainer, SaaS buying platform on the market –– and one that pays for itself.” Ryan Neu, Vendr CEO and co-founder The standard buying process historically wastes time and resources for both software vendors and customers. Vendr enables businesses to maximize the return on their SaaS investments through cost savings and more efficient spend, improving stack visibility across the organization. Composed of the best industry data of more than 2,000 SaaS suppliers, Vendr 2.0 is facilitating critical transformation in how organizations purchase and manage software. Tapping Into Transparency Software buying is a perpetual process and it no longer makes sense to have buying and supplier lifecycle management exist in disparate places. By bringing everything into one place, companies layer the benefits of an expert service team and deep SaaS insights into an integrated system of record that offers unparalleled visibility into their stack. Using Vendr, customers can take a proactive approach to their SaaS spend, equipping their teams with the best software while saving money. Buyer <-> supplier: Vendr offers insights and negotiation support to help buyers and sellers quickly evaluate whether a deal is fair for both sides, ensuring that the process continues moving along internally once it comes time to buy. Buyer <-> procurement function: Vendr provides visibility into internal approval workflows and offers fast-tracked ways to request purchases, leading to smoother relationships between buyers and their company procurement functions. Finance/procurement <-> department heads: With better visibility and faster purchase cycles, stakeholders can easily see the value-add of finance and procurement, ensuring compliance and keeping a handle on costs, leading to better business outcomes for all. This new platform builds upon the competitive advantages that Vendr has in the market as the category creator with the deepest source of supplier insight––based on thousands of deals––as well as the most seasoned negotiators in the industry. Vendr has processed over $1.5B in customer software spend and delivered over $240M in software savings to its customers. To see how much you could be saving on your annual software expense, get in touch here. About Vendr Vendr is changing how companies find, buy and manage SaaS. The first of its kind, Vendr's SaaS buying platform offers both a product and people-powered service to enable the world's fastest-growing companies to purchase software quickly and with guaranteed savings. Today, Vendr has facilitated over $1.5B+ in SaaS purchases across 2,500+ suppliers for Finance and Procurement teams at HubSpot, Brex, Canva, Reddit, Toast, and more. Headquartered in Boston with a second location in Charleston, Vendr was founded in 2019 by Ryan Neu and co-founders Ariel Diaz and Aaron White, who joined the team through the acquisition of Blissfully in 2022. The company has over 250 employees globally

Read More

SOFTWARE

New Relic Brings Error Tracking into Atlassian Open DevOps Solution

New Relic | August 10, 2022

New Relic , the observability company, today announced it has joined the Atlassian Platform Partner Program as part of the Atlassian Open DevOps solution that integrates Jira Software with popular DevOps tools. New Relic has integrated errors inbox with Jira Software to empower developers to easily access and set up full stack error tracking and software performance monitoring from inside Jira Software, Atlassian’s issue and project management tool. With this integration, developers can create Jira Software issues directly within errors inbox, the New Relic platform functionality for error tracking. This announcement coincides with the launch of the Jira Software toolchain page, which helps developer teams to discover and install DevOps tools to improve DevOps practices across their software development lifecycle. “As applications grow more complex, developers need a system in place to proactively fix errors before the customer experience is impacted,” said Peter Pezaris, SVP, Strategy and User Experience at New Relic. “Errors inbox for Jira Software, which builds on the strong history between New Relic and Atlassian, makes developers’ lives easier by allowing them to get to the root cause faster with full error details — including stack traces — and alerts whenever a critical, customer-impacting error arises. Ticketing is made easier, too, as teams can instantly create Jira Software issues with all the right information, without leaving their error management workflow.” Key benefits and capabilities of the New Relic and Jira Software integration include: Track, triage, and resolve errors in one place: Errors are grouped and displayed on a single screen for visibility and easy triaging. Tackle errors across the full application stack with APM, RUM, Mobile, and Serverless (Lambda Functions) data tracked. Resolve errors before impacting customers: Proactively review and triage errors before they affect customers. Get to the root cause faster with full error details, including stack traces and logs in context, provided in the error inbox. Collaborate across teams: Squash bugs as a team with shared error visibility, shared comments, and an integration with Slack. Create Jira Software issues with a click: With the new integration, set up templates and quickly file Jira ​​Software issues containing error details, associated issues, and direct links to the stack trace and entities in New Relic for easy debugging. “Atlassian and New Relic share a vision to improve the developer experience by meeting users where they are and allowing them to use the tools they know and love. “We are excited to include New Relic errors inbox as an app in the Jira Software toolchain page, which makes it easier for millions of users to discover and connect DevOps apps used throughout the software development lifecycle to fill gaps in the toolchain as their DevOps practices evolve.” Bryant Lee, VP of Partnerships and Developer Experience at Atlassian “We have been really impressed with how New Relic errors inbox offers a single place to track all the errors for the entire stack," said Mudit Mehta, Software Engineer II at Postman. "Errors inbox helps developers save time instead of looking and jumping through multiple tools for cloud-based or external error tracking. With the integration for Jira Software, I can quickly view an error and notify the right team members by filing a templated Jira Software issue in seconds without even leaving the New Relic platform.” The Jira Software toolchain page is the latest collaboration between New Relic and Atlassian. The integration builds on the recent launch of the Bitbucket quickstart in New Relic Instant Observability, which gives engineers visibility into the health and performance of their Bitbucket pipelines to continuously improve and optimize their deployments. Developers can also connect Jira Software to New Relic alerts to help the right teams get the right information in the software development life cycle. Errors inbox for Jira Software is available for free to all New Relic full platform users and Jira Cloud users. For more information, visit www.newrelic.com. Additional integrations for Atlassian’s Connect applications with errors inbox and other capabilities will be available later this year. About New Relic As a leader in observability, New Relic empowers engineers with a data-driven approach to planning, building, deploying, and running great software. New Relic delivers the only unified data platform that empowers engineers to get all telemetry—metrics, events, logs, and traces—paired with powerful full stack analysis tools to help engineers do their best work with data, not opinions. Delivered through the industry’s first usage-based consumption pricing that’s intuitive and predictable, New Relic gives engineers more value for the money by helping improve planning cycle times, change failure rates, release frequency, and mean time to resolution. This helps the world’s leading brands including adidas Runtastic, American Red Cross, Australia Post, Banco Inter, Chegg, GoTo Group, Ryanair, Sainsbury’s, Signify Health, TopGolf, and World Fuel Services (WFS) improve uptime, reliability, and operational efficiency to deliver exceptional customer experiences that fuel innovation and growth.

Read More

AI TECH

XSELL Technologies Announces Partnership with Five9 to Deliver Results that Matter

XSELL Technologies | August 09, 2022

XSELL Technologies, a leader in conversational AI for contact center agent optimization, announced that XSELL Agent Experience powered by VoiceStream is available on the Five9 CX Marketplace, empowering customers to amplify top performer outcomes across their contact centers. Leveraging the strength of Five9 cloud contact center solutions, the partnership makes it easy for businesses to integrate XSELL Agent Experience with the Five9 Intelligent Cloud Contact Center. Working together, Five9 and XSELL partnered to deliver real results to a healthcare customer, in the form of $6.9 million in annual incremental profit, an 11% increase in conversion rate and a 52% increase in appointments booked by agents. Read more in the just-published case study: “Health Insurance Provider Uses AI Conversion Maps to Drive Patient Acquisition, Engagement, and Retention with Care at Home.” “We are delighted to bring the power of XSELL Agent Experience to Five9 CX Marketplace to support organizations in their pursuit of a better customer experience while delivering results that matter.” Matt Coughlin, Founder and CEO, XSELL Technologies The Five9 platform facilitates billions of call minutes annually and provides digital engagement, analytics, workflow automation, workforce optimization, and practical AI to create more human customer experiences, engage and empower contact center agents, and deliver tangible business results. XSELL’s AI-powered technology takes a data-driven approach to consistently delivering top performer outcomes by identifying and replicating specialized skill sets, with precision and at scale, across every agent, enterprise-wide. With XSELL Agent Experience, businesses can access AI-generated guidance to improve their customer and agent experience in real-time across the enterprise, driving tangible results like increased NPS scores, decreased Average Handle Time (AHT), and increasing Speed to Proficiency. “Five9 is committed to delivering AI solutions that improve the customer and agent experience, and we are excited to work with partners like XSELL who want to build on our VoiceStream platform to deliver additional innovation and use cases with that same goal in mind,” said Jake Butterbaugh, SVP Global Partner Sales, Five9. XSELL Technologies is sponsoring Five9 CX Summit, taking place Aug. 9-11 at the Aria Resort & Casino in Las Vegas, and will demonstrate XSELL Agent Experience in the CX Hub at the event. Five9 CX Summit is the #1 cloud contact center conference dedicated to making CX work for real life. Learn more about the event, including how to register, here. About XSELL Technologies XSELL Technologies was founded on the belief that the behaviors of the best contact center agents could be learned, replicated, and amplified to every agent in real-time to transform the way that businesses interact with their customers. Today, the XSELL team is partnering with Fortune 50 customers to drive quantifiable improvements in sales results, service metrics, agent engagement, and the overall customer experience.

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