Traffic spikes risked slowing AI responses. Now, infrastructure auto-scales to serve millions of concurrent users instantly.
A technology provider building human-like AI agents for B2C retail and commerce brands that serve millions of global users.
Maintaining high performance for millions of concurrent users required infrastructure that could handle massive demand peaks without latency. The...
“Building a human-like AI agent to serve B2C companies with millions of users is highly competitive, and we needed to ensure our agent was efficient and accurate. Through Google Cloud, we have accessed the latest and greatest technologies and features to overcome these challenges.”
LiveX AI's Customer service agents is part of this use case:
AI agent platform for omnichannel customer engagement across digital and physical channels.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Related implementations across industries and use cases
Viral spikes forced expensive over-provisioning. Autoscaling AI agents now handle 100k+ weekend runs while curbing idle costs.
Infrastructure upkeep drained engineering time. Parallel AI agents now run security audits in 80 seconds, down from 5 minutes.
Sequential models collapsed under messy workflows. A parallel AI engine now clears 40k requests/second with sub-3s response times.
Viral spikes forced expensive over-provisioning. Autoscaling AI agents now handle 100k+ weekend runs while curbing idle costs.
Managing storage consumed engineering bandwidth. Offloading infrastructure let the team focus on algorithms and reach #1 RAG accuracy.
Store managers lost applicants to a 10-day hiring cycle. Now, an AI agent screens and schedules via text, saving thousands of hours.
Shoppers built lists item-by-item. Now, they build full baskets in one prompt, while staff automate internal workflows.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Traffic spikes risked slowing AI responses. Now, infrastructure auto-scales to serve millions of concurrent users instantly.
A technology provider building human-like AI agents for B2C retail and commerce brands that serve millions of global users.
Maintaining high performance for millions of concurrent users required infrastructure that could handle massive demand peaks without latency. The...
“Building a human-like AI agent to serve B2C companies with millions of users is highly competitive, and we needed to ensure our agent was efficient and accurate. Through Google Cloud, we have accessed the latest and greatest technologies and features to overcome these challenges.”
LiveX AI's Customer service agents is part of this use case:
AI agent platform for omnichannel customer engagement across digital and physical channels.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Related implementations across industries and use cases
Viral spikes forced expensive over-provisioning. Autoscaling AI agents now handle 100k+ weekend runs while curbing idle costs.
Infrastructure upkeep drained engineering time. Parallel AI agents now run security audits in 80 seconds, down from 5 minutes.
Sequential models collapsed under messy workflows. A parallel AI engine now clears 40k requests/second with sub-3s response times.
Viral spikes forced expensive over-provisioning. Autoscaling AI agents now handle 100k+ weekend runs while curbing idle costs.
Managing storage consumed engineering bandwidth. Offloading infrastructure let the team focus on algorithms and reach #1 RAG accuracy.
Store managers lost applicants to a 10-day hiring cycle. Now, an AI agent screens and schedules via text, saving thousands of hours.
Shoppers built lists item-by-item. Now, they build full baskets in one prompt, while staff automate internal workflows.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.