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AI-powered code editor with agentic workflows for developers.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.
Local deep packet inspection and network intelligence giving businesses full visibility into application, VPN and Tor traffic.
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
- ✦AI-powered code completion and suggestions
- ✦Automated lint fixing
- ✦Cascade agent for advanced coding assistance
- ✦Integrated app building and deployment
- ✦MCP server support for custom tools
- ✦Terminal command integration
- ✦Memory of codebase structure and workflow
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Automatic context-gathering from connected engineering sources
- ✦AI-generated code, tests and pull requests from tickets
- ✦Task planning that breaks complex work into subtasks
- ✦Auto-updating engineering documentation
- ✦Vector search over embedded project data
- ✦Multiple selectable AI models (GPT, Gemini, Claude, Llama, etc.)
- ✦Engineering productivity analytics dashboard
- ✦Local deep packet inspection agent
- ✦Application identification data feeds
- ✦VPN and Tor IP datasets
- ✦Network informatics and analytics
- ✦Developer documentation
- ✦Asset-based pipeline orchestration
- ✦Built-in lineage and data-quality checks
- ✦Data catalog with asset metadata
- ✦Native dbt, Snowflake and Fivetran integrations
- ✦Branch deployments and hybrid deployment
- ✦Open-source core plus managed Dagster+ cloud
- →Accelerating software development by automating repetitive tasks
- →Reducing onboarding time for new developers
- →Improving code quality and reducing tech debt
- →Streamlining the app building and deployment process
- →Enhancing developer productivity by keeping them in a state of flow
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Engineering teams automating ticket-to-PR workflows
- →Developers wanting AI-assisted debugging and test generation
- →Engineering managers tracking AI-driven productivity gains
- →Teams centralizing documentation from scattered sources
- →Classify application traffic on a network
- →Detect VPN and Tor usage
- →Feed DPI data into security and analytics tools
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms