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All-in-one no-code platform combining forms, workflow automation, AI agents, a database and email in a single subscription.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Data-labeling and RL data platform supplying training data, environments and evaluation for frontier AI labs and enterprises.
AI Text2SQL database client that generates and fixes SQL from natural language across 30+ databases, with dashboards.
No public pricing
No public pricing
No public pricing
No public pricing
Free trial available
- ✦Drag-and-drop form builder with conditional logic
- ✦Workflow automation with 60+ node types and 400+ integrations
- ✦Prebuilt and custom AI agents for tasks like lead scoring
- ✦Relational database with AI-enriched columns
- ✦Drag-and-drop email builder with AI-drafted content
- ✦Company and contact enrichment and web research tools
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦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
- ✦Data labeling across modalities
- ✦RL environments and reward signals
- ✦Custom model evaluations and benchmarks
- ✦Human preference/annotation from an expert network
- ✦Recursion RL platform for enterprise agents
- ✦Robotics data (video, trajectories)
- ✦AI Text2SQL query generation
- ✦One-click SQL error fixing
- ✦GUI database management and ER diagrams
- ✦AI data analysis and dashboards
- ✦Support for 30+ databases
- ✦Local data processing for privacy
- →Capturing and automatically routing sales leads
- →Building onboarding or support-triage workflows
- →Running AI-driven lead scoring and qualification
- →Sending personalized, data-merged email campaigns
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Building training and evaluation datasets
- →Post-training and RLHF for models
- →Benchmarking model capability
- →Training enterprise specialist agents
- →Write SQL from plain language
- →Manage multiple databases in one client
- →Generate BI dashboards from data
- →Migrate and sync schemas/data