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Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.
No public pricing
No public pricing
Free trial available
No public pricing
- ✦Natural-language to Git command suggestions
- ✦AI-driven command matching
- ✦Copy-ready command output
- ✦Git guides and reference
- ✦Contribution and work-quality analytics
- ✦Automated, AI-powered performance reviews
- ✦Retrospective insights
- ✦Operational bottleneck alerts
- ✦Gamification with XP, levels and leaderboards
- ✦Uses Git metadata without accessing source code
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦Spec-driven development (requirements, design, tasks)
- ✦Parallel agents, local or cloud
- ✦Property-based and correctness testing
- ✦Works in IDE, CLI, web and mobile
- ✦Multiple models (Claude, open-weight, Auto)
- ✦Headless CLI for CI/CD
- ✦Context from tools like Figma and Terraform
- ✦Zero-ETL data integration
- ✦Federated Query
- ✦Streaming Ingestion
- ✦Instant Replication with CDC
- ✦API to SQL conversion
- ✦NoSQL to SQL conversion
- ✦SQL to API conversion
- ✦Self-service Integration
- ✦Generate SQL with AI
- →Find the correct Git command quickly
- →Learn Git syntax by describing a goal
- →Avoid memorizing Git flags
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD
- →Query data directly from its source in real-time.
- →Process data wherever it is, blending data from different sources.
- →Ingest streaming data from Kafka, Segment, etc., into Peaka BI Table.
- →Replace nightly batch ingestion with real-time data access.
- →Treat every data source like a relational database by converting APIs to tables.
- →Use SQL to query NoSQL databases.
- →Query consolidated data and expose it with APIs.