With AI agents trained and supported by GKE and NVIDIA AI, LiveX AI can cut customer care expenses by up to 85%.
For consumer companies, offering a positive customer experience is a crucial competitive advantage, but doing so presents a number of difficulties. Even if a website draws visitors, failing to personalize it can make it difficult to turn those visitors into paying clients. Call centers are expensive to run, and long wait times irritate consumers during peak call volumes. Though they are more scalable, traditional chatbots cannot replace a genuine human-to-human interaction.
Google AI agents
At the forefront of generative AI technology, LiveX AI creates personalized, multimodal AI agents with vision, hearing, conversation, and show capabilities to provide customers with experiences that are genuinely human-like. LiveX AI, a company founded by a group of seasoned business owners and eminent IT executives, offers companies dependable AI agents that generate robust consumer engagement on a range of platforms.
Real-time, immersive, human-like customer service is offered by LiveX AI generative AI agents, who respond to queries and concerns from clients in a friendly, conversational style. Additionally, agents must be quick and reliable in order to provide users with a positive experience. A highly efficient and scalable platform that can do away with the response latency that many AI agents have is necessary to create that user experience, especially on busy days like Black Friday.
GKE offers a strong basis for sophisticated generative AI applications
Utilising Google Kubernetes Engine (GKE) and the NVIDIA AI platform, Google Cloud and LiveX AI worked together from the beginning to accelerate LiveX AI’s development. Within three weeks, LiveX AI was able to provide a customized solution for its client thanks to the assistance of Google Cloud. Furthermore, LiveX AI was able to access extra commercial and technical tools as well as have their cloud costs covered while they were getting started by taking part in the Google for Startups Cloud Programme and the NVIDIA Inception programme.
The LiveX AI team selected GKE, which enables them to deploy and run containerized apps at scale on a safe and effective global infrastructure, since it was a reliable solution that would enable them to ramp up quickly. Taking advantage of GKE’s flexible integration with distributed computing and data processing frameworks, training and serving optimized AI workloads on NVIDIA GPUs is made simple by the platform orchestration capabilities of GKE.
GKE Autopilot
Developing multimodal AI agents for companies with enormous quantities of real-time consumer interactions is made easier with GKE Autopilot in particular, since it facilitates the easy scalability of applications to multiple clients. LiveX AI does not need to configure or monitor a Kubernetes cluster’s underlying compute when GKE Autopilot takes care of it.
LiveX AI has achieved over 50% reduced TCO, 25% faster time-to-market, and 66% lower operational costs with the use of GKE Autopilot. This has allowed them to concentrate on providing value to clients rather than setting up or maintaining the system.
Over 50% reduced TCO, 25% quicker time to market, and 66% lower operating costs were all made possible with GKE Autopilot for LiveX AI.
Zepp Health
Zepp Health, a direct-to-consumer (D2C) wellness product maker, is one of these clients. Zepp Health worked with LiveX AI to develop an AI customer agent for their Amazfit wristwatch and smart ring e-commerce website in the United States. In order to provide clients with individualized experiences in real time, the agent had to efficiently handle large numbers of customer interactions.
GKE was coupled with A2 Ultra virtual machines (VMs) running NVIDIA A100 80GB Tensor Core GPUs and NVIDIA NIM inference microservices for the Amazfit project. NIM, which is a component of the NVIDIA AI Enterprise software platform, offers a collection of user-friendly microservices intended for the safe and dependable implementation of high-performance AI model inference.
Applications were upgraded more quickly after they were put into production because to the use of Infrastructure as Code (IaC) techniques in the deployment of NVIDIA NIM Docker containers on GKE. The development and deployment procedures benefited greatly from NVIDIA hardware acceleration technologies, which maximized the effects of hardware optimization.
Amazfit AI
Overall, compared to running the Amazfit AI agent on another well-known inference platform, LiveX AI was able to achieve an astounding 6.1x acceleration in average answer/response generation speed by utilising GKE with NVIDIA NIM and NVIDIA A100 GPUs. Even better, it took only three weeks to complete the project.
Running on GKE with NVIDIA NIM and GPUs produced 6.1x acceleration in average answer/response generation speed for the Amazfit AI agent as compared to another inference platform.
For users of LiveX AI, this Implies
- If effective AI-driven solutions are implemented, customer assistance expenses might be reduced by up to 85%.
- First reaction times have significantly improved, going from hours to only seconds, compared to industry standards.
- Increased customer satisfaction and a 15% decrease in returns as a result of quicker and more accurate remedies
- Five times more lead conversion thanks to a smart, useful AI agent.
Wayne Huang, CEO of Zepp Health, states, “They believe in delivering a personal touch in every customer interaction.” “LiveX AI makes that philosophy a reality by giving their clients who are shopping for Amazfit a smooth and enjoyable experience.
Working together fosters AI innovation
Ultimately, GKE has made it possible for LiveX AI to quickly scale and provide clients with cutting-edge generative AI solutions that yield instant benefits. GKE offers a strong platform for the creation and implementation of cutting-edge generative AI applications since it is a safe, scalable, and affordable solution for managing containerized apps.
It speeds up developer productivity, increases application dependability with automated scaling, load balancing, and self-healing features, and streamlines the development process by making cluster construction and management easy.
