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Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
AI-powered web accessibility platform for ADA/WCAG compliance, blending automated remediation with expert services.
Open-source framework for automated end-to-end UI testing of mobile and web apps, with a paid cloud for parallel device runs.
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
No public pricing
Free trial available
Free trial available
Free trial available
- ✦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
- ✦accessWidget automated AI remediation
- ✦accessScan accessibility auditing
- ✦accessFlow for accessible code
- ✦Screen-reader and keyboard-navigation support
- ✦Expert audits, VPAT and litigation support
- ✦CMS integrations
- ✦Human-readable YAML test flows
- ✦Local CLI and Studio testing for free
- ✦Open-source, CI-friendly design
- ✦Cloud device farm for parallel runs
- ✦AI-agent integration through MCP
- ✦Self-healing tests with local agents
- ✦Asset-based pipeline orchestration
- ✦Built-in lineage and data-quality checks
- ✦Data catalog with asset metadata
- ✦Native dbt, Snowflake and Fivetran integrations
- ✦Branch deployments and hybrid deployment
- ✦Open-source core plus managed Dagster+ cloud
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Achieving ADA/WCAG compliance
- →Reducing accessibility litigation risk
- →Ongoing accessibility monitoring
- →Enterprise-scale accessibility programs
- →Automate mobile app UI regression tests
- →Run tests in parallel across many devices
- →Integrate UI testing into CI pipelines
- →Let AI agents generate and run app tests
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms