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CLI-based personal AI that runs 15+ LLMs from your terminal and pairs with Markdown tools like Obsidian and VS Code.
Terminal-native AI tool (Kane CLI) that turns plain-English descriptions into real-Chrome browser test flows.
IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.
AI coding platform routing many agents and models through one encrypted, usage-based endpoint with CLI, IDE and multi-agent execution.
Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.
No public pricing
No public pricing
- ✦Terminal/CLI interface for prompting LLMs
- ✦Access to 15 models across 7 providers
- ✦Markdown workflow integration (Obsidian, VS Code, MkDocs)
- ✦Situational web-app generation and local run
- ✦Web scraping/content extraction (gather)
- ✦Vision-model support for images
- ✦Configurable prompt templates and intents
- ✦Natural-language browser flow automation from the CLI
- ✦Auto-healing and vision-based element detection
- ✦Integration with a wider agentic test cloud (real devices, visual/accessibility testing)
- ✦MCP server for connecting AI agents into IDEs
- ✦Shareable evidence links for pass/fail results
- ✦Credit-based monthly usage plans
- ✦BYOK access to 15+ model providers
- ✦Agentic planning-then-build mode
- ✦AI autocomplete
- ✦MCP connections to external systems
- ✦Custom rules and live context tracking
- ✦Local models via Ollama/LM Studio
- ✦VS Code and JetBrains plugins
- ✦Unified encrypted inference endpoint
- ✦Multi-agent parallel execution
- ✦CLI, IDE, and API access
- ✦App builder and remote coding agents
- ✦Chairman LLM output evaluation
- ✦35+ IDE integrations
- ✦AI code completion and suggestions
- ✦Natural-language code generation
- ✦In-IDE chat assistance
- ✦AI code review
- ✦IDE integrations (VS Code, JetBrains, etc.)
- ✦GitHub integration
- →Prompt and compare multiple LLMs from the terminal
- →Generate and run small web apps without setup
- →Automate Markdown document workflows
- →Extract structured content from text and webpages
- →Developers running local end-to-end browser tests from a terminal
- →QA teams automating cross-browser regression checks
- →Teams needing tests resilient to UI redesigns
- →IDE-integrated AI test authoring via MCP
- →Code generation, refactoring and debugging
- →Control AI spend with your own keys
- →Switch between frontier models per task
- →Keep code private and data-sovereign
- →Automating refactors, tests, and migrations
- →Running competing AI coding agents
- →Building apps from prompts
- →Integrating agents into CI/CD
- →Speeding up coding with AI completions
- →Generating code from plain-language prompts
- →Getting in-editor help and explanations
- →Reviewing pull requests with AI
- →Understanding unfamiliar codebases