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Pricing
No public pricing
Free trial available
No public pricing
Try Now: $0 for 3 Days
Open Source: $0
Free: $0
Premium: $10/contributor
Free: $0 /month
Popular: $9.99 /month
Enterprise: $49 /month
Core features
- ✦Enhanced Context Engineering for deep codebase analysis and adaptive memory
- ✦Intelligent Agents for autonomous planning, coding, and testing
- ✦Spec-Driven Development for clarifying requirements and automating execution
- ✦Intelligent Codebase Search and Advanced Repository Insight
- ✦Context-aware code completions and next-edit suggestions
- ✦Support for leading AI models (Claude, GPT, Gemini)
- ✦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)
- ✦AI Copilot for code generation
- ✦Web search
- ✦Technical content writing
- ✦Integration with data sources and applications
- ✦Github integration with Claude AI models
- ✦Built-in code editor (IDE)
- ✦Connects to Salesforce, Intercom, and internal databases
- ✦Data-driven Performance Reviews
- ✦AI-Powered Retrospective Insights
- ✦Contribution and Work Quality Analytics
- ✦Operational Bottleneck Alerts
- ✦Gamification (XP, Levels, Achievements, Leaderboard)
- ✦Seamless GitHub and Bitbucket Integration
- ✦LLM-Powered Reporting for features and bug fixes identification
- ✦Scheduled Notifications via email and Slack
- ✦AI Chat for team progress inquiries
- ✦Automated progress insights and development velocity metrics
Use cases
- →Delegating complex software development tasks to AI agents for autonomous completion.
- →Performing multi-file code edits and refactoring through natural language chat.
- →Gaining deep architectural understanding of a codebase to resolve issues with precision.
- →Generating unit tests, code explanations, and uncovering codebase architecture.
- →Systematically tackling software development tasks from planning to testing.
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Code generation
- →Web search
- →Writing technical content
- →Getting insights on codebase
- →Creating conversational AI Assistants
- →Generating SQL queries
- →Creating landing pages and scripts
- →Automating tasks
- →Optimize engineering processes and track team performance.
- →Empower teams with actionable insights and gamified motivation.
- →Gain 360-degree visibility into engineering team performance for data-driven decisions.
- →Acquire, reactivate, and engage open-source contributors.
- →Track pull requests and analyze commits to monitor team progress.
- →Generate automated email and Slack notifications for development updates.
- →Identify features and bug fixes from commit messages and pull request descriptions.
- →Receive intelligent summaries of team progress and development velocity metrics.
- →Understand team activity and project insights without deep technical knowledge.
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