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Enterprise data-annotation and evaluation platform pairing a labeling tool with a managed expert annotator workforce.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
AI tool for engineering teams that automates code review, status updates, and answers questions about what's changing in code.
Open-source, model-agnostic AI code review tool positioned as a CodeRabbit alternative with control over models and costs.
No public pricing
No public pricing
No public pricing
Free trial available
- ✦Customizable multimodal annotation editors for image, video, text and audio
- ✦Support for RLHF preference data, SFT datasets, RAG and agent evaluation workflows
- ✦Managed expert annotator workforce option
- ✦Data curation, exploration and analytics tools
- ✦Team and project management with SSO on higher tiers
- ✦Integrations with AWS, GCP, Databricks, Snowflake and others
- ✦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
- ✦AI code review
- ✦Automatic engineering status updates
- ✦Agent that answers questions and takes action
- ✦Metrics on coding time and project focus
- ✦Pushed vs landed tracking
- ✦Commit and contributor insights
- ✦Model-agnostic reviews with your own API keys (BYOK)
- ✦Custom review rules written in plain language
- ✦Detects rule files from Cursor, Copilot, and Claude
- ✦Business-rule validation from Jira, Linear, and Notion
- ✦Automatic technical-debt tracking
- ✦Engineering delivery metrics dashboard
- ✦Self-hosted or cloud, open source
- →Building large-scale labeled datasets to train computer vision or NLP models
- →Running human evaluation and RLHF pipelines for LLM fine-tuning
- →Auditing and scoring AI agent decisions with human review
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Automating code reviews
- →Keeping stakeholders updated on engineering progress
- →Understanding what's changing in a codebase
- →Tracking team productivity metrics
- →Automated pull-request review
- →Enforcing team-specific code standards
- →Self-hosting AI review to control costs
- →Tracking technical debt and delivery metrics