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Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
Browser extension and AI generator that copies CSS from any site and turns designs or screenshots into code.
Vibe-coding builder creating full-stack apps by chatting with AI.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
Continuously analyzes MySQL, MariaDB, and PostgreSQL workloads to recommend and safely apply configuration and query fixes.
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Free trial available
- ✦150+ recommendations across 50+ AWS services
- ✦Zombie and unused resource cleanup
- ✦Over-provisioned rightsizing
- ✦Idle-resource scheduler
- ✦SpotBot for ECS Fargate spot/on-demand switching
- ✦AWS console extension with Slack/Teams alerts
- ✦Copy CSS/HTML from any website
- ✦Image and screenshot to code
- ✦AI React and HTML generators
- ✦Framework conversion (React, Tailwind, Vue)
- ✦Interactive editor with live preview
- ✦Free HTML-to-JSX and CSS-to-Tailwind tools
- ✦CodeFlying enables full-stack app creation via chat in minutes
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Workload-based configuration tuning
- ✦SQL query analytics and optimization suggestions
- ✦Schema optimization (duplicate/unused index detection)
- ✦24/7 automated health and security monitoring
- ✦One-command agent installation
- ✦Human approval required before applying changes
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
- →Cloning UI elements from live sites
- →Turning mockups into code
- →Generating React components fast
- →Converting CSS to Tailwind
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- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Database teams reducing manual tuning workload
- →Hosting providers optimizing customer databases at scale
- →Engineering teams without a dedicated DBA fixing performance issues
- →AWS RDS users tuning managed database instances