Application Refactoring · IT Operations Automation · Real-time Analytics
Enabling 140,000+ users to turn natural language into working apps with sub-second latency. But this vision was hindered by the company’s previous infrastructure. Builders faced 30–70% higher latency, disrupting the flow of real-time generation. Complex agents, such as Japanese language tutors, suffered from context rot, causing loss of user history and hallucinating answers.
Reported impact
Cuts infrastructure overhead by 45% to fund innovation with Cloud Run; Reduces latency by 30-70% for real-time app generation using Vertex AI; Scales to 13B+ tokens with zero downtime during global events using GKE; Accelerates feature delivery 2x with unified DevOps tools including Cloud Build.
Now, the platform handles requests as diverse as a PE teacher building a volleyball velocity tracker or a Head of Product prototyping a customer feedback app. When a prompt arrives, instantly routes tasks to specialized agents for coding and research. For complex multimodal needs, such as analyzing video motion, Gemini models on Vertex AI generate high-fidelity outputs in real time. To maintain the intelligence of these agents, the platform uses BigQuery as a telemetry layer, tracking billions of tokens to prevent context rot, and Cloud SQL for structured data management. Beneath this workflow, Google Kubernetes Engine (GKE) creates isolated namespaces for each agent graph, ensuring thousands of builders can create simultaneously. and Cloud Functions automatically spin up stateless microservices to handle traffic bursts, while Cloud Load Balancing ensures requests reach the nearest region for sub-second response times.
stored or unified in BigQuery, Cloud Storage, Cloud SQL, processed with Vertex AI, orchestrated via Google Kubernetes Engine (GKE), Cloud Build, and surfaced through Gemini, Cloud Run, Cloud CDN
Accelerates feature delivery 2x with unified DevOps tools including Cloud Build
Cuts infrastructure overhead by 45% to fund innovation with Cloud Run
Enabling 140,000+ users to turn natural language into working apps with sub-second latency.
Reduces latency by 30-70% for real-time app generation using Vertex AI
Scales to 13B+ tokens with zero downtime during global events using GKE
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Traceability
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