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AI video social-listening platform that scans social video content to surface untagged brand mentions, sentiment, and creator leads.
Agentic QA platform that drives a real browser or live API to verify AI-generated code and hands agents a fixable bug report.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Agentic terminal and cloud agent platform (Warp Terminal, Warp Agent, Oz) for developers orchestrating Claude Code, Codex, and other agents.
No public pricing
No public pricing
No public pricing
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦AI video analysis of audio, visuals, and captions
- ✦Untagged brand mention and UGC detection
- ✦Creator sourcing by niche, audience, and brand fit
- ✦Outbound comment engagement tracking
- ✦Competitive benchmarking across brands
- ✦Brand sentiment and safety monitoring
- ✦Live browser/API testing rather than mocked assertions
- ✦Auto-generated failure bundles with root-cause hypotheses
- ✦CLI and MCP/IDE integration for AI coding agents
- ✦Auto-healing tests when the UI drifts
- ✦Growing regression suite that persists across development phases
- ✦No-code web app with live preview and video replay for QA teams
- ✦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
- ✦Modern terminal rebuilt for agentic coding workflows
- ✦Warp Agent with multi-agent orchestration and model routing
- ✦Oz platform for launching agents into the cloud via SDK, CLI, or terminal
- ✦Codebase indexing and granular permission controls
- ✦Team-wide usage visibility and spend/credit caps
- ✦Open-source terminal core
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Finding untagged user-generated content about a brand
- →Sourcing creators that match specific audience criteria
- →Measuring campaign impact across social video
- →Benchmarking a brand's social presence against competitors
- →Verifying AI coding-agent output before merging code
- →Catching regressions from unattended overnight coding runs
- →QA teams testing live apps without writing test scripts
- →Gating CI/CD releases on end-to-end pass rates
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Developers who want an AI-assisted terminal for daily coding
- →Teams orchestrating multiple coding agents (Claude Code, Codex) together
- →Engineering orgs needing governance over agent-driven development
- →Companies moving agent workflows from local machines to the cloud