Customer service teams at fast-growing companies face a challenging reality: customer inquiries are growing exponentially, but scaling human teams at the same pace isn’t always sustainable.
Intelligent AI tools offer a new path forward. They handle routine questions automatically so employees can focus on more complex customer service tasks that require empathy, judgment, and creative problem-solving.
LiveX AI enables businesses to build and deploy advanced AI systems that deliver natural conversational experiences at scale. These can show up as chat bots, call center agents — even 3D holographic personas in live settings.
To handle thousands of concurrent, real-time interactions with low latency requires infrastructure that is both powerful and elastic, especially when seamlessly escalating complex issues to human agents.
In this joint technical post, we’ll share the technical blueprint LiveX AI uses to build and scale its intelligent customer experience systems on Google Cloud, demonstrating how the right combination of services makes this transformation possible.
Why this architecture matters: Proven ROI
This architecture delivers measurable business impact.
90%+ self-service rate for Wyze: Smart home leader Wyze deployed LiveX AI to achieve a 90%+ self-service rate, enabling their support team to focus on complex cases that require human expertise while improving the overall customer experience.
3x conversion for Pictory: The video creation platform Pictory saw a 3x increase in conversions by using LiveX AI to proactively engage and qualify website visitors.
These results are only possible through a sophisticated, scalable, and secure architecture built on Google Cloud.
Platform capabilities designed for scale
The LiveX AI platform is designed to be production-ready, enabling companies to easily deploy intelligent customer experience systems. This is possible through key capabilities, all running on and scaling with Google Cloud’s Cloud Run and Google Kubernetes Engine (GKE):
AgentFlow orchestration: The coordination layer that manages conversation flow, knowledge retrieval, and task execution. It routes routine queries automatically and escalates complex issues to human agents with full context.
Multilingual by design: Built to deliver native-quality responses in over 100 languages, leveraging powerful AI models and Google’s global-scale infrastructure.
Seamless integration: Connects securely to internal and external APIs, enabling the system to access account information, process returns, or manage subscriptions, giving human agents complete context when they step in.
Customizable knowledge grounding: Trained on specific business knowledge to ensure accurate and consistent responses aligned with team expertise.
Natural interface: Deployed via chat, voice, or avatar interfaces across web, mobile, and phone channels.
Figure 1: LiveX real-world 3D assistants
The technical blueprint: Building intelligent customer experience systems on Google Cloud
LiveX AI’s architecture is intelligently layered to optimize for performance, scalability, and cost-efficiency. Here’s how specific Google Cloud services power each layer.
Figure 2: LiveX AI customer service agent architecture on Google Cloud
The front-end layer
Managing real-time communication across web, mobile, and voice channels requires lightweight microservices that handle session management, channel integration, and API gateway services.
Cloud Run is the ideal platform for this workload. As a fully managed, serverless solution, it automatically scales from zero to thousands of instances during traffic spikes, then scales back down, so LiveX AI only pays for the computation they actually use.
The orchestration and AI engine
The platform’s core, AgentFlow, manages the conversational state, interprets customer intent, and coordinates responses. When issues require human expertise, it routes them to agents with complete context. The system processes natural language input to determine customer intent, breaks down requests into multi-step plans, and connects to databases (like Cloud SQL) and external platforms (Stripe, Zendesk, Intercom, Salesforce, Shopify) so both AI and human agents have complete customer context.
Cloud Run for orchestration automatically scales based on request traffic, perfectly handling fluctuating conversational loads with pay-per-use billing.
GKE for AI inference provides the specialized capabilities needed for real-time AI:
GPU management: GKE’s cluster autoscaler dynamically provisions GPU node pools only when needed, preventing costly idle time. Spot VMs significantly reduce training costs.
Hardware acceleration: Seamless integration with NVIDIA GPUs and Google TPUs, with Multi-Instance GPU (MIG) support to maximize utilization of expensive accelerators.
Low latency: Fine-grained control over specialized hardware and the Inference Gateway enable intelligent load balancing for real-time responses.
With this foundation, LiveX AI can serve millions of concurrent users during peak demand while maintaining sub-second response times.
The knowledge and integration layer
From public FAQs to secure account details, the knowledge layer provides all the information the system needs to deliver helpful responses.
The Doc Processor (on Cloud Run) builds and maintains the knowledge base in the vector database for the Retrieval-Augmented Generation (RAG) system, while the API Gateway manages configuration and authentication. For long-term storage, LiveX AI relies on Cloud SQL as the management database, while short-term context is kept in Google Cloud Memorystore.
Putting it all together
Three key advantages emerge from this design: elastic scaling that matches actual demand, cost efficiency through serverless and managed GKE services, and the performance needed for real-time conversational AI at scale.
Looking ahead: Empowering customer experience teams at scale
The future of customer service centers on intelligent systems that amplify what human agents do best: empathy, judgment, and creative problem-solving. Businesses that adopt this approach empower their teams to deliver the personalized attention that builds lasting customer relationships, freed from the burden of repetitive queries.
For teams evaluating AI-powered customer experience systems, this architecture offers a proven blueprint: start with Cloud Run for elastic front-end scaling, leverage GKE for AI inference workloads, and ensure seamless integration with existing platforms.
The LiveX AI and Google Cloud partnership demonstrates how the right platform and infrastructure can transform customer service operations. By combining intelligent automation with elastic, cost-effective infrastructure, businesses can handle exponential inquiry growth while enabling their teams to focus on building lasting customer relationships.
To explore how LiveX AI can help your team scale efficiently, visit the LiveX AI Platform.
- To build your own generative AI applications with the infrastructure powering this solution, get started with GKE and Cloud Run.