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Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Open-source data-labeling and AI-evaluation platform for image, text, audio, video and LLM workflows, with a paid enterprise tier.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
AI design-to-code tool that turns Figma/Adobe XD designs into responsive front-end code for React, HTML/CSS and more.
No public pricing
No public pricing
Free trial available
Free trial available
No public pricing
No public pricing
- ✦CSV to API conversion
- ✦Data parsing (CSV to JSON)
- ✦Filtering capabilities
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦Open-source multi-type labeling
- ✦Programmable, customizable interfaces
- ✦API, SDK and webhooks
- ✦ML backend for pre-labeling and active learning
- ✦LLM evaluation and RLHF workflows
- ✦Enterprise QA, SSO and analytics
- ✦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
- ✦Figma and Adobe XD plugins for design import
- ✦AI conversion of designs to responsive code
- ✦Output to React, React Native, Next.js, HTML/CSS, Vue and more
- ✦Reusable, editable components
- ✦One-click export or sync of generated code
- →Sharing CSV data with a team via an API
- →Creating a public API from CSV data
- →Filtering and accessing specific data within a CSV file programmatically
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Labeling training data across modalities
- →Human-in-the-loop AI evaluation
- →RLHF and fine-tuning data collection
- →RAG and LLM benchmarking
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Turning designs into front-end code faster
- →Prototyping web and mobile UIs from Figma
- →Giving developers a code head-start from designs