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Undetectable desktop AI assistant that feeds real-time answers during coding and technical interviews.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
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
No public pricing
Free trial available
- ✦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
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦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)
- ✦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
- →Getting live help on coding interview problems
- →Answering technical questions in real time
- →Avoiding detection during screen-shared interviews
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →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