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Full-stack observability platform with an AI SRE agent that detects, debugs, and auto-fixes issues across infra, apps, and users.
Local deep packet inspection and network intelligence giving businesses full visibility into application, VPN and Tor traffic.
AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
AI coding platform routing many agents and models through one encrypted, usage-based endpoint with CLI, IDE and multi-agent execution.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦Infrastructure and application performance monitoring
- ✦Log monitoring with AI insights
- ✦Real user monitoring
- ✦OpsAI SRE agent for detection and auto-fix
- ✦Synthetic and browser testing
- ✦LLM observability
- ✦Local deep packet inspection agent
- ✦Application identification data feeds
- ✦VPN and Tor IP datasets
- ✦Network informatics and analytics
- ✦Developer documentation
- ✦Chat-to-app and website generation
- ✦Real-time prototype building
- ✦One-click deploy and hosting
- ✦Templates to start projects
- ✦Credit-based building with shared workspaces
- ✦You own your code and data
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Unified encrypted inference endpoint
- ✦Multi-agent parallel execution
- ✦CLI, IDE, and API access
- ✦App builder and remote coding agents
- ✦Chairman LLM output evaluation
- ✦35+ IDE integrations
- →Monitor full-stack app and infra health
- →Debug incidents faster with AI
- →Correlate frontend and backend issues
- →Observe Kubernetes and cloud environments
- →Classify application traffic on a network
- →Detect VPN and Tor usage
- →Feed DPI data into security and analytics tools
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Automating refactors, tests, and migrations
- →Running competing AI coding agents
- →Building apps from prompts
- →Integrating agents into CI/CD
