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Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
No-code chatbot builder that trains an AI assistant on business data for support, sales, and lead capture across web and messaging apps.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
No public pricing
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
- ✦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)
- ✦Automated service discovery and dependency topology mapping
- ✦SLO-based alert triage and prioritization
- ✦AI-driven root cause analysis with pre-built workflows
- ✦Human-approved remediation with full audit trails
- ✦Works alongside existing tools like Datadog, Grafana, New Relic
- ✦Governance and policy enforcement layer for agent actions
- ✦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
- ✦Train chatbot on uploaded documents, website pages, and live data sources
- ✦Embed widget on any website
- ✦Deploy across WhatsApp, Messenger, and Slack
- ✦Live agent takeover with chat summaries
- ✦Custom bot persona and brand voice
- ✦API-based tools for real-time data lookups
- ✦Meeting/appointment booking automation
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →SRE teams reducing mean-time-to-resolution during incidents
- →Platform engineers wanting policy-governed AI infrastructure management
- →Enterprises needing SOC 2 / PCI / HIPAA-compliant AI operations
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Automating 24/7 customer support replies
- →Answering pre-sale questions to boost conversions
- →Collecting leads and scheduling meetings
- →Summarizing chats for human agent handoff
- →Building an internal knowledge assistant for staff
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site