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All-in-one no-code platform combining forms, workflow automation, AI agents, a database and email in a single subscription.
Undetectable desktop AI assistant that feeds real-time answers during coding and technical interviews.
Data-labeling and RL data platform supplying training data, environments and evaluation for frontier AI labs and enterprises.
Vibe-coding builder creating full-stack apps by chatting with AI.
AI prototyping tool that generates UI matching your design system, letting product teams test features fast.
No public pricing
No public pricing
No public pricing
- ✦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
- ✦Real-time AI answers during technical interviews
- ✦Invisible to screen sharing and recording
- ✦Hidden from dock, tray and activity monitor
- ✦Click-through overlay
- ✦Live audio capture and transcription
- ✦Lifetime unlimited access license
- ✦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)
- ✦CodeFlying enables full-stack app creation via chat in minutes
- ✦AI UI generation from prompts
- ✦Match existing styling and design systems
- ✦Rapid, high-fidelity prototyping
- ✦Live team editing and sharing
- ✦Enterprise security and compliance
- →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
- →Getting live help on coding interview problems
- →Answering technical questions in real time
- →Avoiding detection during screen-shared interviews
- →Building training and evaluation datasets
- →Post-training and RLHF for models
- →Benchmarking model capability
- →Training enterprise specialist agents
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- →Prototype new product features
- →Test designs with customers
- →Build design-system-consistent mockups