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All-in-one no-code platform combining forms, workflow automation, AI agents, a database and email in a single subscription.
Free tool that auto-generates conversational, browsable documentation for any public GitHub repo, from the makers of Devin.
Text-to-SQL tool that writes dialect-aware queries and gives AI agents governed, read-only database access.
Turns Git commits and PRs into AI-summarized daily or weekly reports delivered to Slack or email, no source access.
No public pricing
No public pricing
Free trial available
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
- ✦AI-generated documentation for GitHub repos
- ✦Conversational Q&A about a codebase
- ✦Browsable index of popular repositories
- ✦Deep code indexing via Devin
- ✦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)
- ✦Natural-language to SQL
- ✦Semantic schema layer
- ✦Governed MCP/REST gateway
- ✦Read-only query enforcement
- ✦7 database connectors
- ✦SQL explain, optimize and format
- ✦AI-summarized commit and PR reports
- ✦Daily and weekly scheduled digests
- ✦Slack and email delivery
- ✦One-click OAuth or webhook setup
- ✦GitHub, GitLab and Bitbucket support
- ✦Templates for standups and reports
- →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
- →Understanding an unfamiliar codebase quickly
- →Onboarding to open-source projects
- →Answering questions about repo internals
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Generating SQL without coding
- →Giving agents safe DB access
- →Explaining and fixing queries
- →Querying live databases
- →Keep stakeholders updated on what shipped
- →Replace manual status updates and standups
- →Give teams visibility into Git activity