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Open-source SDK and viewer for logging, querying, and visualizing multimodal robotics data, with a paid managed Hub for scale.
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.
Low-code integration platform for connecting thousands of APIs into workflows and AI agents, including an MCP tool server.
AI web design tool that turns designs into live websites.
No public pricing
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No public pricing
No public pricing
- ✦Open-source Python, Rust, and C++ logging SDK
- ✦Interactive desktop and web viewer for reviewing recordings
- ✦SQL and dataframe queries across logged data
- ✦Column-chunk .rrd storage format for multimodal data
- ✦PyTorch dataloader for training directly on recordings
- ✦Commercial Hub with managed catalog, SSO, and byte-range indexing
- ✦Used in robotics projects like LeRobot, Brush, and PyCuVSLAM
- ✦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
- ✦Visual and code-based workflow builder
- ✦Prebuilt AI agent builder and deployment
- ✦Managed authentication across thousands of apps
- ✦MCP server exposing integrations as agent tools
- ✦Scheduled and event-triggered workflows
- ✦Connect SDK for embedding integrations into other products
- ✦AI-powered design suggestions
- ✦Automated task completion
- ✦Responsive design adaptation
- ✦Instant website conversion
- →Robotics teams debugging calibration and training runs
- →Visualizing and querying large multimodal sensor datasets
- →Streaming training data mixes directly to GPUs at scale
- →Sharing annotated recordings across a robotics engineering team
- →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
- →Building AI agents that call external APIs and tools
- →Automating cross-app workflows such as Slack, Gmail, or Sheets notifications
- →Embedding third-party integrations into a SaaS product
- →Prototyping event-driven automations without heavy infrastructure
- →Designing and launching modern, responsive websites quickly and efficiently.