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Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
AI SQL query optimization tool for developers to detect performance bottlenecks and get explainable tuning recommendations.
Free trial available
No public pricing
Free trial available
No public pricing
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
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- ✦Zero-configuration SQL optimization across multiple database engines
- ✦AI-powered query rewriting engine
- ✦Bottleneck detection with smart index recommendations
- ✦Dual-pane SQL diff viewer for before/after comparison
- ✦AI query plan explainer with step-by-step reasoning
- ✦MyBatis XML auto-rewrite support
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Backend developers speeding up slow production queries
- →Teams reducing manual SQL tuning workload
- →Engineers wanting explainable reasoning behind optimization suggestions
- →Companies standardizing query performance across MySQL/PostgreSQL systems