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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.
AI SQL query optimization tool for developers to detect performance bottlenecks and get explainable tuning recommendations.
No public pricing
No public pricing
No public pricing
Free trial available
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦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)
- ✦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
- ✦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
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →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
- →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