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AI Pine Script generator for TradingView strategies and indicators.
AI coding platform and IDE that orchestrates multiple agent sessions and lets teams plug in their own AI subscriptions.
Connects Git repos to answer plain-English questions about your code with file references and dependency context.
AI prototyping tool that generates UI matching your design system, letting product teams test features fast.
Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
No public pricing
No public pricing
- ✦AI-powered Pine Script code generation
- ✦Custom strategy and indicator creation
- ✦Error correction and code optimization
- ✦TradingView integration
- ✦AI coding IDE with agent orchestration
- ✦Run and manage multiple agent sessions
- ✦Task, artifact and collaboration tools
- ✦Bring-your-own AI subscription or API keys
- ✦Cloud-scale agent execution
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦AI UI generation from prompts
- ✦Match existing styling and design systems
- ✦Rapid, high-fidelity prototyping
- ✦Live team editing and sharing
- ✦Enterprise security and compliance
- ✦Persistent, structured memory built as a knowledge graph
- ✦Sub-300ms hybrid retrieval (RAG) with reranking
- ✦Native filesystem mount for agent memory access
- ✦Connectors to Slack, Notion, Drive, Gmail, GitHub, S3
- ✦Automatic extraction from PDFs, images, and audio
- ✦User profile and behavior tracking across sessions
- →Generating custom trading strategies for backtesting on TradingView
- →Creating custom indicators for technical analysis
- →Automating the process of writing Pine Script code
- →Shipping code faster with AI agents
- →Coordinating agent work across a team
- →Managing tasks and artifacts in one place
- →Running many parallel agent sessions
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Prototype new product features
- →Test designs with customers
- →Build design-system-consistent mockups
- →Developers adding long-term memory to AI agents
- →Teams building agents that need to sync with existing tools
- →Individuals wanting one memory layer shared across multiple AI assistants