Cloudflare Workers AI

Top Builders

Explore the top contributors showcasing the highest number of app submissions within our community.

Cloudflare Workers AI

Run machine learning models, powered by serverless GPUs, on Cloudflare's global network. Workers AI allows you to run AI models in a serverless way, without having to worry about scaling, maintaining, or paying for unused infrastructure. You can invoke models running on GPUs on Cloudflare's network from your own code â€” from Workers, Pages, or anywhere via the Cloudflare API.

General
Author	Cloudflare, Inc.
Website	Cloudflare Workers AI
Documentation	https://developers.cloudflare.com/workers-ai/
Type	Serverless AI Inference Platform
Launch Year	2023
GPU Network	180+ cities globally

Features

50+ Open-Source Models

Text generation (Llama, Mistral, and more)
Text embeddings and classification
Image generation and classification
Automatic speech recognition
Translation models
Object detection capabilities

Serverless Infrastructure

Pay-for-what-you-use pricing model
Automatic scaling with demand
No infrastructure management required
Fast cold start times with V8 isolates

Global Edge Network

AI inference close to users for low latency
Models available in 180+ cities worldwide
Reduced network bottlenecks
Consistent performance globally

Developer Platform Integration

Seamless integration with Cloudflare Workers
Works with Pages for full-stack AI applications
REST API for platform-agnostic access
Integration with Vectorize (vector database)
AI Gateway for monitoring and control

Key Capabilities

Edge AI Computing: Run AI models at the network edge for minimal latency
Serverless GPU Access: Access powerful GPU infrastructure without provisioning
Model Catalog: Curated selection of popular open-source AI models
Real-time Inference: Low-latency AI processing for interactive applications
Global Deployment: Deploy once, run everywhere on Cloudflare's network
Integrated Ecosystem: Works with R2 storage, D1 database, and other Cloudflare services

Use Cases

Building AI-powered chatbots and conversational interfaces
Real-time content moderation and classification
Image and video processing at scale
Personalization and recommendation engines
Automated translation and localization
Voice recognition and text-to-speech applications
RAG (Retrieval-Augmented Generation) systems
AI-powered API endpoints and microservices

Supported Model Categories

Large Language Models: For text generation and chat applications
Embedding Models: For semantic search and similarity matching
Image Models: For generation, classification, and analysis
Speech Models: For transcription and synthesis
Vision Models: For object detection and recognition
Translation Models: For multilingual content processing

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Cloudflare Cloudflare Workers AI AI technology Hackathon projects

Discover innovative solutions crafted with Cloudflare Cloudflare Workers AI AI technology, developed by our community members during our engaging hackathons.

Executor

Executor is an autonomous meeting-to-execution enforcement system built for enterprise teams that lose accountability after meetings. Most AI meeting tools stop at summaries, but Executor continues into execution by extracting commitments, identifying owners, deadlines, priorities, and source quotes, then turning those decisions into tracked work. Users can upload transcripts or run live meetings with Speechmatics real-time transcription. Gemini analyzes the meeting, extracts structured action items, scores execution risk, and powers follow-up drafting. Each commitment can be synced directly into Jira, Asana, and Notion, connecting meeting decisions to the tools teams already use. Executor also runs a background enforcement agent deployed on Vultr. The monitor checks deadlines every six hours, marks overdue commitments, drafts follow-up emails, retries failed sends, and escalates to managers after repeated missed follow-ups. Human review remains available before sensitive messages are sent, while every autonomous action is stored in an audit log. The application is deployed publicly on Cloudflare Workers, uses Supabase for authentication and database storage, Gemini for reasoning, Speechmatics for voice transcription, and Vultr for the scheduled enforcement worker. Executor closes the gap between “we decided” and “it actually got done.”

AI Virtual Puppet Theater

AI Virtual Puppet Theater is an immersive AI powered browser experience that transforms users into live digital puppeteers through real time gesture control, facial tracking, and cinematic storytelling. The project combines computer vision, realtime animation, and interactive stage design to create a magical virtual theater where users control expressive 3D characters using natural human movements. Using webcam based hand tracking and facial detection, players can perform combat, emotional reactions, celebration animations, and cinematic interactions. The system tracks gestures, blinking, eye movement, facial expressions, and head motion to make puppet characters feel emotionally alive and deeply connected to the user. Characters react dynamically with expressive eyes, animated emotions, smooth movement interpolation, and theatrical body language. The platform includes a complete cinematic story mode featuring dramatic sequences between a King, Lion, Hero, and mysterious dark creature, brought to life through curtain transitions, realtime lighting, particle systems, and synchronized animation, all running directly inside the browser. The technical stack includes Next.js, TypeScript, Tailwind CSS, React Three Fiber, Three.js, Zustand, MediaPipe, TensorFlow.js, face-api.js, and Framer Motion, with strong focus on low latency interaction and immersive presentation quality.

AI WAFS web application firewall

What Would Blow Our Minds ● A guardrail system that stops prompt injection without blocking legitimate use ● AI that reasons about adversarial intent like a security expert ● Something that adapts to new attack patterns automatically ● Multi-layered defence that validates inputs, outputs, and behaviour ● A system that makes AI agents safe to deploy on the public internet ● Defence that explains WHY something was blocked in human-understandable terms Why This Matters Now AI agents are being deployed in production with access to sensitive data and critical actions: ● Prompt injection is the SQL injection of the AI era ● AI agents can take real-world actions - making attacks more dangerous ● Traditional security tools weren't designed for natural language inputs ● New attack techniques emerge faster than manual defences can adapt ● Organisations need guardrails before widespread AI deployment creates security incidents AI can be used to detect and defend against AI-specific attacks using adversarial reasoning andintent analysis.

Vibe Studio: AI-Native Agentic IDE

Vibe Studio represents a paradigm shift in how developers interact with Artificial Intelligence. Most current solutions are merely basic chat wrappers grafted onto existing code editors, lacking true integration with the development lifecycle. Vibe Studio, however, is built from the ground up as an AI-native Integrated Development Environment featuring a custom Agentic UI. At its core, Vibe Studio replaces the standard "prompt-and-pray" approach with a deterministic, event-driven architecture. We implemented an asynchronous Pub/Sub execution bus and a rigorous state machine (RoadmapTracker) that orchestrates complex, multi-step LLM workflows. This means the AI doesn't just spit out code snippets; it follows a structured lifecycle—from architectural analysis to implementation, and verification. Our platform is designed for senior engineers who demand control. The human architect sets the constraints, defines the patterns, and dictates the workflow, while the autonomous agents handle the mechanical execution. Features include real-time intent-guard pipelines to prevent prompt contamination and strict architectural enforcement. Vibe Studio isn't just another coding assistant; it is a robust, production-grade infrastructure designed to scale developer output without sacrificing engineering fundamentals.

CodeGuardian.AI

CodeGuardian.AI is a unified developer platform designed to simplify software maintenance, improve security, and accelerate the entire development lifecycle. Instead of relying on multiple disconnected tools for testing, vulnerability scanning, modernization, and architecture analysis, CodeGuardian.AI brings everything together into a single AI-driven workspace powered by IBM Bob MCP integrations. The platform intelligently analyzes repositories to identify outdated coding patterns, risky dependencies, hidden edge cases, and structural bottlenecks. It can automatically generate modernization suggestions, create advanced edge-case test suites, detect security vulnerabilities mapped to CWE standards, and explain findings in plain English for developers of all skill levels. Interactive architecture visualizations also help teams understand large codebases faster and onboard new contributors more efficiently. Built with a modern TypeScript-based stack using Next.js, Express, TailwindCSS, and React Flow, the project focuses heavily on usability, scalability, and production-quality engineering. CodeGuardian AI aims to become a future-ready AI engineering assistant that helps teams ship secure, reliable, and maintainable software with greater confidence and significantly reduced debugging and QA effort.