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AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
AI Text2SQL database client that generates and fixes SQL from natural language across 30+ databases, with dashboards.
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
Free trial available
- ✦CSV to API conversion
- ✦Data parsing (CSV to JSON)
- ✦Filtering capabilities
- ✦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
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- ✦AI Text2SQL query generation
- ✦One-click SQL error fixing
- ✦GUI database management and ER diagrams
- ✦AI data analysis and dashboards
- ✦Support for 30+ databases
- ✦Local data processing for privacy
- →Sharing CSV data with a team via an API
- →Creating a public API from CSV data
- →Filtering and accessing specific data within a CSV file programmatically
- →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
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Write SQL from plain language
- →Manage multiple databases in one client
- →Generate BI dashboards from data
- →Migrate and sync schemas/data