Demos and architectures

A practical example of how these services come together in a real fullstack application architecture.

Store user-generated content in R2 for fast, secure, and cost-effective architecture.

This diagram showcases Cloudflare components optimizing connected transportation systems. It illustrates how their technologies minimize latency, ensure reliability, and strengthen security for critical data flow.

You can connect a Cloudflare Worker to get data from Google BigQuery and pass it to Workers AI, to run AI Models, powered by serverless GPUs.

By shifting features such as rate limiting, caching, and error handling to the proxy layer, organizations can apply unified configurations across services and inference service providers.

The architecture diagram illustrates how AI applications can be built end-to-end on Cloudflare, or single services can be integrated with external infrastructure and services.

AI systems combine text-generation and text-to-image models to create visual content from text. They generate prompts, moderate content, and produce images for various applications.

RAG combines retrieval with generative models for better text. It uses external knowledge to create factual, relevant responses, improving coherence and accuracy in NLP tasks like chatbots.

By integrating automatic speech recognition technology into video platforms, content creators, publishers, and distributors can reach a broader audience, including individuals with hearing impairments or those who prefer to consume content in different languages.

Leverage various components of Cloudflare's ecosystem to construct a scalable image management solution