How to Secure your Web Applications

January 30, 2019 | 53 views

If you want to protect your apps against threats, first you need to understand them. This video will briefly and concisely walk you through each tier of an application, what makes those tiers vulnerable to attacks, and how to secure them and reduce your risk. Learn how to protect your apps with F5’s full security portfolio—explore use cases, product capabilities, and deployment modes.

Spotlight

TetraNoodle Technologies

TetraNoodle Technologies is a boutique big data and AI consulting company that provides strategic insights and develops problem-solving digital solutions for businesses of all sizes. They build solutions for cloud, desktop, mobile platforms as well as IoT devices. For the past 25 years, they have been able to work with some of the biggest companies, notably IBM, Microsoft, Pearson Education, Canada Health Infoway, University of British Columbia, Desire2Learn, and many more.

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SOFTWARE

AI's Impact on Improving Customer Experience

Article | July 13, 2022

To enhance the consumer experience, businesses all over the world are experimenting with artificial intelligenace (AI), machine learning, and advanced analytics. Artificial intelligence (AI) is becoming increasingly popular among marketers and salespeople, and it has become a vital tool for businesses that want to offer their customers a hyper-personalized, outstanding experience. Customer relationship management (CRM) and customer data platform (CDP) software that has been upgraded with AI has made AI accessible to businesses without the exorbitant expenses previously associated with the technology. When AI and machine learning are used in conjunction for collecting and analyzing social, historical, and behavioral data, brands may develop a much more thorough understanding of their customers. In addition, AI can predict client behavior because it continuously learns from the data it analyzes, in contrast to traditional data analytics tools. As a result, businesses may deliver highly pertinent content, boost sales, and enhance the customer experience. Predictive Behavior Analysis and Real-time Decision Making Real-time decisioning is the capacity to act quickly and based on the most up-to-date information available, such as information from a customer's most recent encounter with a company. For instance, Precognitive's Decision-AI uses a combination of AI and machine learning to assess any event in real-time with a response time of less than 200 milliseconds. Precognitive's fraud prevention product includes Decision-AI, which can be implemented using an API on a website. Marketing to customers can be done more successfully by using real-time decisioning. For example, brands may display highly tailored, pertinent content and offer to clients by utilizing AI and real-time decisioning to discover and comprehend a customer's purpose from the data they produce in real-time. By providing deeper insights into what has already happened and what can be done to facilitate a sale through suggestions for related products and accessories, AI and predictive analytics are able to go further than historical data alone. This increases the relevance of the customer experience, increases the likelihood that a sale will be made, and increases the emotional connection that the customer has with a brand.

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AI TECH

The Evolution of Quantum Computing and What its Future Beholds

Article | July 20, 2022

The mechanism of quantum computers will be entirely different from anything we humans have ever created or constructed in the past. Quantum computers, like classical computers, are designed to address problems in the real world. They process data in a unique way, though, which makes them a much more effective machine than any computer in use today. Superposition and entanglement, two fundamental ideas in quantum mechanics, could be used to explain what makes quantum computers unique. The goal of quantum computing research is to find a technique to accelerate the execution of lengthy chains of computer instructions. This method of execution would take advantage of a quantum physics event that is frequently observed but does not appear to make much sense when written out. When this fundamental objective of quantum computing is accomplished, and all theorists are confident works in practice, computing will undoubtedly undergo a revolution. Quantum computing promises that it will enable us to address specific issues that current classical computers cannot resolve in a timely manner. While not a cure-all for all computer issues, quantum computing is adequate for most "needle in a haystack" search and optimization issues. Quantum Computing and Its Deployment Only the big hyperscalers and a few hardware vendors offer quantum computer emulators and limited-sized quantum computers as a cloud service. Quantum computers are used for compute-intensive, non-latency-sensitive issues. Quantum computer architectures can't handle massive data sizes yet. In many circumstances, a hybrid quantum-classical computer is used. Quantum computers don't use much electricity to compute but need cryogenic refrigerators to sustain superconducting temperatures. Networking and Quantum Software Stacks Many quantum computing software stacks virtualize the hardware and build a virtual layer of logical qubits. Software stacks provide compilers that transform high-level programming structures into low-level assembly commands that operate on logical qubits. In addition, software stack suppliers are designing domain-specific application-level templates for quantum computing. The software layer hides complexity without affecting quantum computing hardware performance or mobility.

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SOFTWARE

Language Models: Emerging Types and Why They Matter

Article | August 8, 2022

Language model systems, often known as text understanding and generation systems, are the newest trend in business. However, not every language model is made equal. A few are starting to take center stage, including massive general-purpose models like OpenAI's GPT-3 and models tailored for specific jobs. There is a third type of model at the edge that is intended to run on Internet of Things devices and workstations but is typically very compressed in size and has few functionalities. Large Language Models Large language models, which can reach tens of petabytes in size, are trained on vast volumes of text data. As a result, they rank among the models with the highest number of parameters, where a "parameter" is a value the model can alter on its own as it gains knowledge. The model's parameters, which are made of components learned from prior training data, fundamentally describe the model's aptitude for solving a particular task, like producing text. Fine-tuned Language Models Compared to their massive language model siblings, fine-tuned models are typically smaller. Examples include OpenAI's Codex, a version of GPT-3 that is specifically tailored for programming jobs. Codex is both smaller than OpenAI and more effective at creating and completing strings of computer code, although it still has billions of parameters. The performance of a model, like its capacity to generate protein sequences or respond to queries, can be improved through fine-tuning. Edge Language Models Edge models, which are intentionally small in size, occasionally take the shape of finely tuned models. To work within certain hardware limits, they are occasionally trained from scratch on modest data sets. In any event, edge models provide several advantages that massive language models simply cannot match, notwithstanding their limitations in some areas. The main factor is cost. There are no cloud usage fees with an edge approach that operates locally and offline. As significant, fine-tuned, and edge language models grow in response to new research, they are likely to encounter hurdles on their way to wider use. For example, compared to training a model from the start, fine-tuning requires less data, but fine-tuning still requires a dataset.

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SOFTWARE

Low-code and No-code: A Business' New Best Friend

Article | July 5, 2022

Businesses are starting to integrate artificial intelligence (AI) into their workflow in greater numbers as a result of the growth of digital transformation and developments in machine learning (ML). As a result, platforms that need no coding, as well as their low-code counterparts, are becoming more popular. This development is a step toward computer science's long-term objective of automating manual coding. Low-code/no-code AI platforms will be beneficial to businesses in more data-driven industries like marketing, sales, and finance. AI can assist in a variety of ways, including automating invoicing, evaluating reports, making intelligent suggestions, and anticipating churn rates. How Does an Organization Look at Low-code/No-code as the Future? Developers and other tech-related positions are in high demand, particularly in the fields of AI and data science. Organizations have the chance to close the gap with the aid of citizen data scientists who don't require an AI professional to design unique AI solutions for many scenarios, thanks to low-code and no-code AI technologies. The demand for technological solutions and AI technologies is rising significantly as the technological landscape rapidly changes. AI systems, for example, require complex software that uses a lot of code, a variety of frameworks, and the Internet of Things (IoT). One person's capacity to comprehend every technical detail is strained by the array of complicated technology. Software delivery must be timely, effective, and secure while maintaining high standards. Conclusion Low-code AI solutions offer the speed, ease of use, and adaptability of ready-made software solutions while also drastically reducing the time to market for AI solutions and the cost of recruiting software and computer vision engineers. Organizations are free to construct the architecture, functionality, or pipeline that best suits their project, the sky being the limit. However, creating such unique models may be both costly and time-consuming. Therefore, employing low-code/no-code platforms would apply to particular pipeline actions that would streamline and accelerate the processes.

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Spotlight

TetraNoodle Technologies

TetraNoodle Technologies is a boutique big data and AI consulting company that provides strategic insights and develops problem-solving digital solutions for businesses of all sizes. They build solutions for cloud, desktop, mobile platforms as well as IoT devices. For the past 25 years, they have been able to work with some of the biggest companies, notably IBM, Microsoft, Pearson Education, Canada Health Infoway, University of British Columbia, Desire2Learn, and many more.

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SOFTWARE,COMPUTER VISION

Deci Introduces World’s Most Advanced Semantic Segmentation Models

Deci | September 26, 2022

Deci, the deep learning company harnessing AI to build AI, today announced a new set of industry-leading semantic segmentation models, dubbed DeciSeg. Deci’s proprietary Automated Neural Architecture Construction (AutoNAC) technology automatically generated semantic segmentation models that significantly outperform the most powerful models publicly available, such as the MobileViT released by Apple, and the DeepLab family released by Google. Deci’s models deliver more than 2x lower latency, as well as 3-7% higher accuracy. Semantic segmentation is one of the most widely used computer vision tasks across many business verticals, including automotive, smart cities, healthcare, and consumer applications, and is often required for many edge AI applications. However, significant barriers exist to running semantic segmentation models directly on edge devices, such as high latency and the inability to deploy those models due to their size. With DeciSeg models, semantic segmentation tasks that previously could not be carried out at the edge because they were too resource intensive are now possible. This allows companies to develop new use cases and applications on edge devices, reduce inference costs (since AI practitioners will no longer need to run these tasks in expensive cloud environments), open new markets, and shorten development times. “DeciSegs are an example of the power of Deci’s AutoNAC engine capabilities to generate custom hardware-aware deep learning models with unparalleled performance on any hardware. AI teams can easily use DeciSegs models or leverage Deci’s AutoNAC engine to build and deploy custom models that run real-time computer vision tasks on their edge devices.” said Yonatan Geifman, PhD, co-founder and CEO of Deci. Deci’s platform has a proven-track record in enabling AI at the edge and empowering AI teams to build and deploy production grade deep learning models. Earlier this year, Deci announced the discovery of DeciNets for CPUs, which reduced the gap between a model’s inference performance on a GPU versus a CPU by half, without sacrificing the model’s accuracy, enabling AI to run on lower cost, resource constrained hardware. “In the world of automated deep neural network design and construction, Deci’s AutoNAC technology is a game changer. It uses deep learning to search vast spaces of neural networks for the model most appropriate for a particular task and particular AI chip. In this case, AutoNAC was applied to the Pascal VOC Semantic Segmentation task on NVIDIA’s Jetson Xavier NX™ chip and we are very pleased with the results.” said Ran El-Yaniv, co-founder and Chief Scientist of Deci and Professor of Computer Science at the Technion – Israel Institute of Technology. Deci’s platform is serving customers across industries in various production environments including edge, mobile, data centers and cloud. To learn more about how leading AI teams leverage Deci’s platform to build production grade models and accelerate inference performance, visit here. About Deci Deci enables deep learning to live up to its true potential by using AI to build better AI. With the company's deep learning development platform, AI developers can build, optimize, and deploy faster and more accurate models for any environment including cloud, edge, and mobile, allowing them to revolutionize industries with innovative products. The platform is powered by Deci's proprietary automated Neural Architecture Construction technology (AutoNAC), which automatically generates and optimizes deep learning models' architecture and allows teams to accelerate inference performance, enable new use cases on limited hardware, shorten development cycles and reduce computing costs. Founded by Yonatan Geifman, Jonathan Elial, and Professor Ran El-Yaniv, Deci's team of deep learning engineers and scientists are dedicated to eliminating production-related bottlenecks across the AI lifecycle.

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AI TECH,GENERAL AI,AI APPLICATIONS

tekVizion Uses Amazon Web Services to Bring Conversational AI to Contact Centers

tekvizion | September 21, 2022

tekVizion is working with Amazon Web Services (AWS) to make it easy for enterprises to add conversational artificial intelligence (AI), such as bots and interactive voice response systems (IVRs), to their existing contact center platforms. With the solution, IT administrators can quickly improve caller experience and reduce agent handle times without the cost and disruption of upgrading their entire contact center. The tekVizion 360 solution leverages two primary AWS services: Amazon Lex and the Amazon Chime SDK. Amazon Lex is an AWS service with advanced natural language models to design, build, test, and deploy conversational interfaces in applications. The Amazon Chime SDK lets builders easily add real-time voice, video, and messaging into their applications. The Amazon Chime SDK is pre-integrated with Amazon Lex and common enterprise voice infrastructure, so you can easily add conversational experiences to contact centers that support the Session Initiation Protocol (SIP) for voice communication. “Working together with the AWS team, tekVizion built a solution to reduce the burden on call center agents and administrators with conversational AI. Amazon Lex will assist customers with minor requests and improve the entire user experience.” Chakra Devalla, CEO of tekVizion Combining tekVizion’s call center expertise and AWS’s capabilities in automation and AI enables contact centers to focus on critical issues, improved end user experience, faster resolution time, and easing burdens on internal teams. In addition, tekVizion continuously tests the contact center platform and Amazon Lex integration with powerful testing tools combined with their industry-leading interoperability lab for contact center and testing experts. “Today’s customers want instant, personalized, and effective resolutions for their problems,” said Sid Rao, General Manager of Amazon Chime SDK at Amazon Web Services, Inc. “What makes tekVizion’s solution innovative is their ability to use the Amazon Chime SDK to capture the intelligent results from Amazon Lex and integrate these results with third-party on-premises and cloud contact center platforms and agent desktops. By harnessing Amazon Lex’s speech-to-text and natural language understanding features, tekVizion customers can deploy conversational interactive voice response systems that improve call containment, customer engagement, and customer satisfaction scores.” About tekVizion PVS, Inc tekVizion is an independent, global testing lab that provides hundreds of multi-vendor end to end solution validation, certification and integration testing to service providers, vendors, and enterprises. tekVizion’s testing helps accelerate the time to value, improve product quality and future proof investments in business communications.

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SOFTWARE,FUTURE TECH

Khoros Expands with AWS, Joins AWS ISV Accelerate Program and AWS Marketplace

Khoros | August 30, 2022

Khoros, an award-winning leader in digital-first customer engagement software and services, today announced expanded work with Amazon Web Services (AWS) by joining the AWS Independent Software Vendors (ISV) Accelerate Program and launching in AWS Marketplace. The AWS ISV Accelerate Program is a co-sell program for organizations that provide software solutions that run on, or integrate with, AWS. The program helps Khoros support a broader set of customers and connect closely with the AWS Sales organization. The Khoros platform is also now available in the AWS Marketplace, a digital catalog that makes it easy for customers to find, test, buy, and deploy software that runs on AWS. For Khoros, participation in the AWS ISV Accelerate Program and AWS Marketplace strengthens its relationship with AWS, building upon a recent announcement that Khoros's digital contact center solution works with Amazon Connect. Khoros, built on AWS, seamlessly blends the three modes of contact center communication—voice, synchronous chat, and asynchronous messaging—in one unified desktop for consistent customer and agent experiences. Khoros’s digital contact center solution works with Amazon Connect combining both digital and voice solutions in a single interface. By supporting AWS services, including Amazon Connect, Amazon Lex, Amazon Translate, and Amazon Transcribe, Khoros offers a truly omnichannel experience. This solution allows agents and contact center leaders to deliver exceptional customer experiences via messaging, social, email, and voice in a unified experience. Additionally, it helps them transcribe voice to text, make agile changes to interactive voice response (IVR) automation, and manage inbound and outbound calls—all within the Khoros platform. AWS ISV Accelerate Program members are held to the industry’s highest standards and must undergo a comprehensive evaluation to gain acceptance into the program. Khoros participated in a thorough architectural and security review to ensure the quality and design of its solutions. Proof of customer excellence was also reviewed to validate the successes Khoros customers have achieved across industry verticals. “We’re excited to expand our relationship with AWS and offer our platform to even more enterprises globally. Customers demand tailored, personalized engagement with brands, and we have the technology that empowers brands to do just that and more. Leveraging AI and our intuitively elegant agent experience, our platform harnesses every customer interaction so agents can build trust and drive satisfaction and retention.” Chris Tranquill, CEO of Khoros Khoros is unique in the industry in coupling its omnichannel expertise with 20 years of digital-first innovation, valuable voice of customer (VoC) insights, award-winning outbound marketing capabilities, and enterprise-grade communities software—all powered by its patent-pending data-powered foundation. With Khoros, contact centers can improve their customer experience (CX), increase agent efficiency, and reduce traditional contact center costs. About Khoros The Khoros award-winning customer engagement platform helps over 2,000 global brands, including one-third of the Fortune 100 companies, create customers for life. With over 20 patented technologies, Khoros connects every facet of customer engagement, including digital contact centers, messaging, chat, online brand communities, CX analytics, and social media management. Combined with our top-rated services, the Khoros platform enables brands to connect with customers throughout their entire digital journey.

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SOFTWARE,COMPUTER VISION

Deci Introduces World’s Most Advanced Semantic Segmentation Models

Deci | September 26, 2022

Deci, the deep learning company harnessing AI to build AI, today announced a new set of industry-leading semantic segmentation models, dubbed DeciSeg. Deci’s proprietary Automated Neural Architecture Construction (AutoNAC) technology automatically generated semantic segmentation models that significantly outperform the most powerful models publicly available, such as the MobileViT released by Apple, and the DeepLab family released by Google. Deci’s models deliver more than 2x lower latency, as well as 3-7% higher accuracy. Semantic segmentation is one of the most widely used computer vision tasks across many business verticals, including automotive, smart cities, healthcare, and consumer applications, and is often required for many edge AI applications. However, significant barriers exist to running semantic segmentation models directly on edge devices, such as high latency and the inability to deploy those models due to their size. With DeciSeg models, semantic segmentation tasks that previously could not be carried out at the edge because they were too resource intensive are now possible. This allows companies to develop new use cases and applications on edge devices, reduce inference costs (since AI practitioners will no longer need to run these tasks in expensive cloud environments), open new markets, and shorten development times. “DeciSegs are an example of the power of Deci’s AutoNAC engine capabilities to generate custom hardware-aware deep learning models with unparalleled performance on any hardware. AI teams can easily use DeciSegs models or leverage Deci’s AutoNAC engine to build and deploy custom models that run real-time computer vision tasks on their edge devices.” said Yonatan Geifman, PhD, co-founder and CEO of Deci. Deci’s platform has a proven-track record in enabling AI at the edge and empowering AI teams to build and deploy production grade deep learning models. Earlier this year, Deci announced the discovery of DeciNets for CPUs, which reduced the gap between a model’s inference performance on a GPU versus a CPU by half, without sacrificing the model’s accuracy, enabling AI to run on lower cost, resource constrained hardware. “In the world of automated deep neural network design and construction, Deci’s AutoNAC technology is a game changer. It uses deep learning to search vast spaces of neural networks for the model most appropriate for a particular task and particular AI chip. In this case, AutoNAC was applied to the Pascal VOC Semantic Segmentation task on NVIDIA’s Jetson Xavier NX™ chip and we are very pleased with the results.” said Ran El-Yaniv, co-founder and Chief Scientist of Deci and Professor of Computer Science at the Technion – Israel Institute of Technology. Deci’s platform is serving customers across industries in various production environments including edge, mobile, data centers and cloud. To learn more about how leading AI teams leverage Deci’s platform to build production grade models and accelerate inference performance, visit here. About Deci Deci enables deep learning to live up to its true potential by using AI to build better AI. With the company's deep learning development platform, AI developers can build, optimize, and deploy faster and more accurate models for any environment including cloud, edge, and mobile, allowing them to revolutionize industries with innovative products. The platform is powered by Deci's proprietary automated Neural Architecture Construction technology (AutoNAC), which automatically generates and optimizes deep learning models' architecture and allows teams to accelerate inference performance, enable new use cases on limited hardware, shorten development cycles and reduce computing costs. Founded by Yonatan Geifman, Jonathan Elial, and Professor Ran El-Yaniv, Deci's team of deep learning engineers and scientists are dedicated to eliminating production-related bottlenecks across the AI lifecycle.

Read More

AI TECH,GENERAL AI,AI APPLICATIONS

tekVizion Uses Amazon Web Services to Bring Conversational AI to Contact Centers

tekvizion | September 21, 2022

tekVizion is working with Amazon Web Services (AWS) to make it easy for enterprises to add conversational artificial intelligence (AI), such as bots and interactive voice response systems (IVRs), to their existing contact center platforms. With the solution, IT administrators can quickly improve caller experience and reduce agent handle times without the cost and disruption of upgrading their entire contact center. The tekVizion 360 solution leverages two primary AWS services: Amazon Lex and the Amazon Chime SDK. Amazon Lex is an AWS service with advanced natural language models to design, build, test, and deploy conversational interfaces in applications. The Amazon Chime SDK lets builders easily add real-time voice, video, and messaging into their applications. The Amazon Chime SDK is pre-integrated with Amazon Lex and common enterprise voice infrastructure, so you can easily add conversational experiences to contact centers that support the Session Initiation Protocol (SIP) for voice communication. “Working together with the AWS team, tekVizion built a solution to reduce the burden on call center agents and administrators with conversational AI. Amazon Lex will assist customers with minor requests and improve the entire user experience.” Chakra Devalla, CEO of tekVizion Combining tekVizion’s call center expertise and AWS’s capabilities in automation and AI enables contact centers to focus on critical issues, improved end user experience, faster resolution time, and easing burdens on internal teams. In addition, tekVizion continuously tests the contact center platform and Amazon Lex integration with powerful testing tools combined with their industry-leading interoperability lab for contact center and testing experts. “Today’s customers want instant, personalized, and effective resolutions for their problems,” said Sid Rao, General Manager of Amazon Chime SDK at Amazon Web Services, Inc. “What makes tekVizion’s solution innovative is their ability to use the Amazon Chime SDK to capture the intelligent results from Amazon Lex and integrate these results with third-party on-premises and cloud contact center platforms and agent desktops. By harnessing Amazon Lex’s speech-to-text and natural language understanding features, tekVizion customers can deploy conversational interactive voice response systems that improve call containment, customer engagement, and customer satisfaction scores.” About tekVizion PVS, Inc tekVizion is an independent, global testing lab that provides hundreds of multi-vendor end to end solution validation, certification and integration testing to service providers, vendors, and enterprises. tekVizion’s testing helps accelerate the time to value, improve product quality and future proof investments in business communications.

Read More

SOFTWARE,FUTURE TECH

Khoros Expands with AWS, Joins AWS ISV Accelerate Program and AWS Marketplace

Khoros | August 30, 2022

Khoros, an award-winning leader in digital-first customer engagement software and services, today announced expanded work with Amazon Web Services (AWS) by joining the AWS Independent Software Vendors (ISV) Accelerate Program and launching in AWS Marketplace. The AWS ISV Accelerate Program is a co-sell program for organizations that provide software solutions that run on, or integrate with, AWS. The program helps Khoros support a broader set of customers and connect closely with the AWS Sales organization. The Khoros platform is also now available in the AWS Marketplace, a digital catalog that makes it easy for customers to find, test, buy, and deploy software that runs on AWS. For Khoros, participation in the AWS ISV Accelerate Program and AWS Marketplace strengthens its relationship with AWS, building upon a recent announcement that Khoros's digital contact center solution works with Amazon Connect. Khoros, built on AWS, seamlessly blends the three modes of contact center communication—voice, synchronous chat, and asynchronous messaging—in one unified desktop for consistent customer and agent experiences. Khoros’s digital contact center solution works with Amazon Connect combining both digital and voice solutions in a single interface. By supporting AWS services, including Amazon Connect, Amazon Lex, Amazon Translate, and Amazon Transcribe, Khoros offers a truly omnichannel experience. This solution allows agents and contact center leaders to deliver exceptional customer experiences via messaging, social, email, and voice in a unified experience. Additionally, it helps them transcribe voice to text, make agile changes to interactive voice response (IVR) automation, and manage inbound and outbound calls—all within the Khoros platform. AWS ISV Accelerate Program members are held to the industry’s highest standards and must undergo a comprehensive evaluation to gain acceptance into the program. Khoros participated in a thorough architectural and security review to ensure the quality and design of its solutions. Proof of customer excellence was also reviewed to validate the successes Khoros customers have achieved across industry verticals. “We’re excited to expand our relationship with AWS and offer our platform to even more enterprises globally. Customers demand tailored, personalized engagement with brands, and we have the technology that empowers brands to do just that and more. Leveraging AI and our intuitively elegant agent experience, our platform harnesses every customer interaction so agents can build trust and drive satisfaction and retention.” Chris Tranquill, CEO of Khoros Khoros is unique in the industry in coupling its omnichannel expertise with 20 years of digital-first innovation, valuable voice of customer (VoC) insights, award-winning outbound marketing capabilities, and enterprise-grade communities software—all powered by its patent-pending data-powered foundation. With Khoros, contact centers can improve their customer experience (CX), increase agent efficiency, and reduce traditional contact center costs. About Khoros The Khoros award-winning customer engagement platform helps over 2,000 global brands, including one-third of the Fortune 100 companies, create customers for life. With over 20 patented technologies, Khoros connects every facet of customer engagement, including digital contact centers, messaging, chat, online brand communities, CX analytics, and social media management. Combined with our top-rated services, the Khoros platform enables brands to connect with customers throughout their entire digital journey.

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