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AI operating system for car dealerships with voice AI, a smart inbox and agents that capture leads and lift service revenue.
Free tool that auto-generates conversational, browsable documentation for any public GitHub repo, from the makers of Devin.
Local desktop app that assembles code-context prompts for LLMs, with API integrations, token tracking, and prompt saving.
Agentic coding platform (Cosmos) that runs software-dev agents at org scale, using a codebase context engine to cut token cost.
No public pricing
No public pricing
No public pricing
Free trial available
- ✦Voice AI with full customer context
- ✦AI-native Smart Inbox across channels
- ✦LiveCSI real-time satisfaction monitoring
- ✦Service Advisor Agent
- ✦Heat Case and Opportunity Agents
- ✦Mobile app
- ✦Coding education platform for beginners
- ✦Curriculum on Next.js, Vercel, and AI
- ✦AI-powered app development
- ✦Live events and hackathons
- ✦Coding community
- ✦AI-centric platform for software engineers
- ✦Nia AI for code understanding
- ✦Context management and codebase understanding tools
- ✦AI-generated documentation for GitHub repos
- ✦Conversational Q&A about a codebase
- ✦Browsable index of popular repositories
- ✦Deep code indexing via Devin
- ✦Source-code context and prompt management
- ✦Custom and formatting instructions
- ✦BYOK API integrations (OpenAI, Claude, Gemini, etc.)
- ✦Token-limit tracking
- ✦Code-edit feature with visual diffs and backups
- ✦Local, offline prompt generation
- ✦Context Engine for codebase understanding
- ✦Agents across the full SDLC
- ✦Model routing / bring-your-own-keys
- ✦Automated code review and test coverage
- ✦CLI, MCP and native tool integrations
- ✦Enterprise security (SOC 2, ISO 42001, SSO)
- →Answering dealership calls and messages
- →Rescuing and booking service leads
- →Resolving customer complaints (heat cases)
- →Boosting service-advisor productivity
- →Learning to code and build AI-powered applications
- →Developing AI agents that can work with code safely and effectively
- →Empowering developers to orchestrate AI agents across the software lifecycle
- →Improving context management and codebase understanding for AI agents
- →Understanding an unfamiliar codebase quickly
- →Onboarding to open-source projects
- →Answering questions about repo internals
- →Building context-rich prompts for AI coding
- →Comparing model outputs on the same task
- →Reusing saved prompts across tech stacks
- →Keeping code private during prompt creation
- →Automating PR code review
- →Raising test coverage
- →Incident investigation and remediation
- →Large-scale migrations and onboarding