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AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
End-to-end computer vision platform for teams annotating data, training YOLO models, and deploying them at scale.
AI chatbot builder that trains a support agent on your website content in minutes to deflect tickets and capture leads with cited answers.
Unified API that gives AI agents web scraping, search, document extraction, and social/enrichment data through one billed endpoint.
No public pricing
No public pricing
No public pricing
- ✦Chat-to-app and website generation
- ✦Real-time prototype building
- ✦One-click deploy and hosting
- ✦Templates to start projects
- ✦Credit-based building with shared workspaces
- ✦You own your code and data
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Smart data annotation with SAM-powered one-click masks across six task types
- ✦Cloud training with 22+ GPU configurations from RTX 2000 Ada to B200
- ✦Support for YOLOv5 through YOLO26 model families
- ✦One-click deployment across 43 global regions with auto-scaling
- ✦Export to 18 formats including ONNX, TensorRT, and CoreML
- ✦Live training metrics and experiment comparison dashboard
- ✦Fast setup trained directly on website content
- ✦Answers cited back to source content
- ✦Inbound lead capture with automated follow-up
- ✦Integrations with existing support/marketing stack
- ✦Self-improving responses over time
- ✦Unified API for search, scrape, and extraction
- ✦Smart routing across multiple data providers
- ✦Document and PDF structured extraction
- ✦Social and media data (YouTube, TikTok, LinkedIn, reviews)
- ✦People and company enrichment
- ✦MCP and CLI surfaces for AI tools
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Building and training custom object detection or segmentation models
- →Labeling large image/video datasets for computer vision projects
- →Deploying vision models to edge or mobile devices
- →Running quality control or defect detection in manufacturing
- →Powering retail, logistics, or agriculture vision applications
- →SaaS companies deflecting repetitive support questions
- →Marketing teams capturing and qualifying leads via chat
- →Support teams wanting AI answers backed by verifiable sources
- →Feeding AI agents reliable external web data
- →Replacing several scraping and search subscriptions
- →Extracting structured data from PDFs and documents
- →Enriching leads with company and email data