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Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
Talent marketplace linking AI labs with 257,000+ vetted data labelers and trainers for RLHF, red-teaming and evaluation.
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No public pricing
- ✦Serverless GPU compute defined in Python
- ✦Sub-second container cold starts
- ✦Autoscale 0 to 1000+ GPUs
- ✦Inference, training and batch workloads
- ✦Secure sandboxes for untrusted code
- ✦Built-in logging and observability
- ✦Contribution and work-quality analytics
- ✦Automated, AI-powered performance reviews
- ✦Retrospective insights
- ✦Operational bottleneck alerts
- ✦Gamification with XP, levels and leaderboards
- ✦Uses Git metadata without accessing source code
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦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
- ✦Network of 257,000+ pre-vetted AI data experts
- ✦AI-matched shortlists with skills tests and interviews
- ✦Bring talent into any annotation platform, no lock-in
- ✦Self-service or fully managed engagements
- ✦Job feed aggregating 20+ platforms for freelancers
- →Deploying and scaling model inference
- →Fine-tuning and training models
- →Running batch/parallel AI jobs
- →Executing untrusted code in sandboxes
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →Sourcing experts for RLHF and model evaluation
- →Staffing red-teaming and data-labeling projects
- →Scaling annotation teams into existing tools
- →Finding AI training gigs as a freelancer