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All-in-one no-code platform combining forms, workflow automation, AI agents, a database and email in a single subscription.
AI-first customer-service helpdesk built around the Fin AI agent, for support teams handling omnichannel conversations.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Google-owned hub for data scientists to find datasets, enter ML competitions, run notebooks, and learn.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
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
- ✦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)
- ✦Fin AI agent for customer service
- ✦Omnichannel agent inbox
- ✦AI-assisted ticketing
- ✦Copilot agent assistant
- ✦AI conversation insights and scoring
- ✦No-code automations
- ✦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
- ✦Public dataset repository
- ✦Machine-learning competitions with prizes
- ✦Browser-based notebooks with free GPU/TPU
- ✦Micro-courses on data science topics
- ✦Community forums and shared code
- →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
- →Automating customer support with AI
- →Assisting human agents in real time
- →Routing and resolving tickets
- →Analyzing support quality and trends
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Practicing and benchmarking ML models
- →Finding datasets for analysis
- →Competing in predictive-modeling contests
- →Learning data science skills
- →Sharing reproducible notebooks
