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All-in-one no-code platform combining forms, workflow automation, AI agents, a database and email in a single subscription.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Open-source, plugin-based ChatGPT command-line toolkit for AI commit messages, shell commands and translation in the terminal.
AI SQL toolkit for analysts and developers to generate, optimize, validate, format and explain queries across 30+ database engines.
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
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
- ✦npm-installable ChatGPT CLI
- ✦AI-generated Git commit messages
- ✦Natural-language to shell commands
- ✦AI translation plugin
- ✦Extensible plugin system
- ✦Build custom AI CLI workflows
- ✦Natural-language to SQL/NoSQL query generation
- ✦AI-driven query optimization with rewrite suggestions
- ✦Syntax validation with automated error fixes
- ✦Query formatting and cross-engine conversion
- ✦Schema-aware data source connections with autosuggest
- ✦Rule-based guardrails per connected data source
- ✦Support for large schemas with 900+ tables
- →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
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Writing commit messages automatically
- →Turning plain English into terminal commands
- →Translating text from the command line
- →Creating personal AI CLI tools
- →Analysts writing SQL without deep query-syntax knowledge
- →Developers debugging and optimizing slow queries
- →Teams standardizing SQL formatting across a codebase
- →Migrating queries between database engines
- →Learners wanting plain-language explanations of SQL statements