AI TECH Launches SmartAssist, the World’s First AI-Native End-to-End Contact Center as-a-Service Solution | September 28, 2021, a top conversational AI software company, today announced the launch of SmartAssist, the world’s first AI-native end-to-end Contact Center as-a-Service [CCaaS] solution. The solution comes integrated with the Agent Assist virtual assistant to help live agents understand past history/context, as well as an intuitive desktop console that enables agents to easily manage conversations.

Long hold and wait times can anger already frustrated customers, creating a poor user experience and negatively impacting customer satisfaction. Further, employing a full staff of live agents on a 24/7 basis is not only costly but also inefficient and prone to errors and increased wait times. Built on’s enterprise-grade no-code conversational AI platform, SmartAssist accurately responds to the most sophisticated conversations across voice or digital channels, automatically escalating conversations to live agents with seamless contextual continuity to move conversations forward towards successful outcomes.

SmartAssist introduces game-changing agent assistance by leveraging a combination of an Agent Assist virtual assistant to help the live agent with past history/context along with an agent desktop console, a one-stop console for the agent to manage the conversation. Available now, SmartAssist is the industry's first automation-first platform available on-premises or as a service.

" SmartAssist empowers modern day contact centers to deliver an optimized customer and agent experience, efficiently resolving customers issues via voice or digital channels. SmartAssist delivers on the promise of an AI-native contact-center that can be deployed quickly and flexibly, while also giving live agents a single workspace for comprehensive AI-powered assistance."

Raj Koneru, Founder and CEO of

Key features of SmartAssist include:
  • Automation. SmartAssist automates up to 80% of calls and chats without ever reaching a live agent, resulting in increased customer satisfaction and a superior customer experience. Faster resolution lowers average handling time (AHT) and drives efficiency through the enterprise.
  • Agent Assistance. SmartAssist empowers agents to provide phenomenal customer service with Agent Desktop and AgentAssist, leading to an increase in CSAT, decrease in agent attrition and reduced support costs.
  • Flexibly Deploy and Manage. This AI-native solution is built with flexibility in mind. Based on individual customer needs and preferences, it can be deployed to complement your existing telephony system with just the modules you need or can be deployed as a comprehensive, standalone contact center solution. SmartAssist is the only Contact Center as-a-Service [CCaaS] solution in the world that is both AI-native and integrates automation and agent assistance components into one complete end-to-end solution. While traditional IVR vendors “bolt on” an AI automation layer on top of legacy IVR systems, SmartAssist uses AI-native technology from the ground up using the company's unmatched [ML]+2 Natural Language Understanding (NLU) engines.

About increases the speed of business by automating customer and employee experiences through digital virtual assistants built on its market-leading conversational AI platform. Companies who prioritize customer and employee experiences use’s no-code platform to raise NPS and lower operational costs. The top four banks, top three healthcare businesses in the U.S., and over 100 global 2000 companies have automated a billion interactions since was founded in 2014, and its pre-built industry-specific and functional virtual assistants have made it easier and faster for these top-performing businesses to scale the impact of front office automation. has been recognized as a leader by top analysts and ensures the success of its customers through a very fast-growing team headquartered in Orlando with offices in India, the UK, Japan, and Europe.


A common question today is whether moving workloads to the public cloud is a good decision or a bad decision. While this question is understandable, it is the wrong question to ask. Public cloud computing has considerable advantages over physical on-premises equipment solutions, including lower deployment costs and rapid turn-up of new applications. On the other hand, there are drawbacks including security and performance concerns, vendor lock-in, lack of network visibility, and lack of infrastructure control.

Other News

DataRobot Selected by U.S. Department of Defense to Power Government’s AI Initiatives

DataRobot | February 14, 2022

AI Cloud leader DataRobot today announced its selection as an AI partner under a five-year $249 million-ceiling Blanket Purchase Agreement (BPA) awarded by the U.S. Department of Defense (DoD) Joint Artificial Intelligence Center (JAIC). Through this contract, DataRobot is tasked with transforming AI throughout the DoD ecosystem by providing its AI Cloud platform and services to accelerate the government’s use of emerging AI technologies including Machine Learning (ML), Deep Learning (DL), and Neural Networks (NN). DataRobot will support JAIC’s commitment to strategic and world-class AI solutions by: Providing a unified AI platform to enable all users across the DoD to quickly and successfully build and deploy mission-enabling AI projects Detecting, measuring, and standardizing bias prevention as a routine step in the machine learning process, driving more reliable operations and strategic solutions Operationalizing solutions for Testing and Evaluation (T&E) of AI-enabled systems, automated products, and autonomous systems Integrating AI T&E tools and services in alignment with JAIC’s architectures, technical standards, and security standards DataRobot’s end-to-end AI Cloud platform brings together disparate data and users, spanning expert data scientists to IT operators to analysts, through enhanced collaboration and continuous optimization across the entire AI lifecycle. Built as a multi-cloud platform, DataRobot AI Cloud can be deployed in a combination of public clouds, data centers, or at the edge, with governance to protect and secure even the most highly-regulated organizations. AI has the power to shape the next generation of U.S. Defense operations, ensuring the safety of our citizens, personnel and allies. We’re proud to support the JAIC’s mission to maximize the full potential of AI, and we share the DoD’s commitment to solving complex and mission-critical problems with better, faster, data-driven solutions that are accessible for all.” Jim Watson, VP, Sales, Federal & Public Sector, DataRobot About DataRobot DataRobot AI Cloud is the next generation of AI. DataRobot’s AI Cloud vision is to bring together all data types, all users, and all environments to deliver critical business insights for every organization. DataRobot is trusted by global customers across industries and verticals, including a third of the Fortune 50

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Aqua Extends its Alliance with Red Hat and IBM to Bring Cloud Native Security to the Red Hat Marketplace

Aqua Security | August 04, 2020

Aqua Security, the pure-play cloud native security leader, today announced that its Cloud Native Security Platform is available through Red Hat® Marketplace, an open cloud marketplace that makes it easier to discover and access certified software for container-based environments across the hybrid cloud. Built in partnership by Red Hat and IBM, Red Hat Marketplace is designed to meet the unique needs of developers, procurement teams and IT leaders through simplified and streamlined access to popular enterprise software products, including the Aqua Platform. The Aqua Platform provides full visibility into application activity, allowing organizations to detect and prevent suspicious activity and attacks, providing transparent, automated security while helping to enforce policy and simplify regulatory compliance. Aqua’s native integration with OpenShift provides a full-stack security solution for our joint customers, automating security controls in CI/CDs like OpenShift Pipelines and enforcing application immutability in production.

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Deci Launches Version 2.0 of its Deep Learning Development Platform, to Democratize the Power of NAS and Eliminate the AI Efficiency Gap

Deci | May 13, 2022

Deci, the deep learning company harnessing AI to build AI, today launched Version 2.0 of its deep learning development platform, making it easier than ever before for AI developers to build, optimize, and deploy computer vision models on any hardware and environment including cloud, edge and mobile with outstanding accuracy and runtime performance. AI developers face an uphill struggle developing production-ready deep learning models for deployment. These challenges can be largely attributed to the AI efficiency gap facing the industry in which algorithms are growing more powerful and complex, but available compute power is not keeping pace. This gap also creates financial barriers by making the deep learning development and processing more cumbersome and expensive. While Neural Architecture Search (NAS) has been presented as a potential solution to automate the design of superior artificial neural networks that can outperform manually-designed architectures, the resource requirements to operate such technology is excessive. To date, NAS has only been successfully implemented by tech giants like Google, Microsoft and in the confines of academia, proving its impracticality for the vast majority of developers. In order to solve this problem, Deci’s platform, powered by its proprietary NAS engine called AutoNAC (Automated Neural Architecture Construction), enables AI developers to automatically and affordably build efficient computer vision models that deliver the highest accuracy for any given inference hardware, speed, size and targets. Models generated by Deci outperform other known state-of-the-art (SOTA) architectures by a factor of 3x-10x. Developers can start their projects with pre-trained and optimized models (DeciNets) that were generated by the AutoNAC engine for a wide range of hardware and computer vision tasks or use the AutoNAC engine to generate more custom architectures that are tailored for their specific use-cases. In addition, the platform supports teams with a wide range of tools required to develop deep learning-based applications including a hardware-aware model zoo to easily select and benchmark models and hardware, SuperGradients - an open source training library with proven recipes for faster training, automated runtime optimizations, model packaging and more. By using Deci’s platform, AI developers achieve improved inference performance and efficiency to enable deployment on resource constrained edge devices, maximize hardware utilization and reduce training and inference cost. The entire development cycle is shortened and the uncertainty of how the model will deploy on the inference hardware is eliminated. “The new version of Deci’s deep learning platform makes hardware-aware NAS technology accessible to AI teams of any size, helping them eliminate complexities and focus on what they do best - build innovative computer vision applications. We take pride in the fact that the deep learning models generated by Deci's platform are powering AI-based applications of some of the leading enterprises worldwide. We are excited to unleash this powerful engine to help make computer vision even more widely available. Only then can we truly achieve a world where AI advances humanity without limitations, finally making AI affordable, accessible and scalable for all.” Yonatan Geifman, co-founder and CEO of Deci With Deci’s Version 2.0 platform, AI developers can: Easily benchmark models and inference hardware: With Deci’s hardware-aware model zoo, developers can quickly measure inference time of pre-trained and optimized models on and various hardware including edge devices via Deci’s SaaS platform. Simplify the hardware and model selection process by eliminating the need to manually setup and test various combinations of models and hardware. Generate Tailored SOTA CNN Architectures: Automatically find accurate & efficient architectures tailored for the application, hardware and performance targets with Deci’s AutoNAC engine. Simplify Training with SuperGradients: Leverage proven hyperparameter recipes and with Deci’s PyTorch based open source training library called SuperGradients. Automated Runtime Optimization: Automatically compile and quantize your models and evaluate different production settings. Deploy with a Few Lines of Code: Developers can deploy their deep learning workloads on any environment with the Deci’s python based inference engine. Deci’s platform includes three tiers: Free Community Tier: For data scientists and ML engineers looking to find the best models, simplify hardware evaluation and boost runtime performance. Professional Tier: For deep learning teams looking to quickly achieve production grade inference performance and shorten development time. Enterprise Tier: For deep learning experts looking to meet specific performance goals for highly customized use cases. 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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RedFlag Mass Notification for Microsoft Teams is now available on Microsoft AppSource

Pocketstop | January 15, 2022

In the event of a critical situation, communicating quickly and effectively to the desired recipients via a multi-channel communication approach is necessary. Within the US, over 700,000 companies use Microsoft 365 which includes Teams as part of its suite of products. Pocketstop is excited to announce the RedFlag + Microsoft Teams integration and a fourth main channel for alerts is now available. By adding the ability to connect via Microsoft Teams in addition to text, voice, and email, RedFlag provides companies an even greater ability to disrupt and ensure the message reaches the intended recipient. Messages sent via RedFlag to Teams are delivered as both a desktop and mobile push notification to their Teams app, no matter their location or device. Leveraging Teams offers the functionality of sending to the other main channels, whether it is a message with links or attachments, adding a conference number to join a call, or an action-based message requiring a response. This is a powerful additional channel to help when time matters, and RedFlag is the only system to send mass notifications via Teams. It is important to communicate to employees the way they consume information. The Teams integration allows us to reach our employees in an additional way, We have some employees that only communicate via Teams, so this ensures our messaging is heard." Will Gott, Human Resource Manager at Wood-Mizer. For more details on the RedFlag + Teams integration, click here, or see the RedFlag listing on Microsoft AppSource. As a Microsoft Silver Partner, The Teams integration deepens RedFlag's existing Microsoft Integration, ensuring Microsoft users can communicate quickly and securely with an ease of setup and integration not available in other platforms. Current Microsoft + RedFlag users are now able to: Extend their reach worldwide via app notifications through the Microsoft Teams app Use the Active Directory sync to automatically import and continuously synchronize recipient data (Coming Soon) Enjoy Single Sign On for ease of use and security Quickly send multi-channel messages right within Outlook via the add-in Be confident in security, reliability, and scalability because RedFlag is built on Microsoft Azure About Pocketstop Pocketstop is a communication software solutions company empowering companies to create personalized, automated messages designed to provide rapid ROI, backed by the industry's best support at a cost customers can afford.

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A common question today is whether moving workloads to the public cloud is a good decision or a bad decision. While this question is understandable, it is the wrong question to ask. Public cloud computing has considerable advantages over physical on-premises equipment solutions, including lower deployment costs and rapid turn-up of new applications. On the other hand, there are drawbacks including security and performance concerns, vendor lock-in, lack of network visibility, and lack of infrastructure control.