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Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Full-stack platform for web scraping, data extraction, and automation; category leader.
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.
IBM's open, hybrid data lakehouse that connects, governs and optimizes enterprise data to make it AI-ready across clouds and on-premises.
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Web scraping
- ✦Data extraction
- ✦Browser automation
- ✦AI agents
- ✦Anti-blocking
- ✦Proxy rotation
- ✦Open-source tools (Crawlee)
- ✦Ready-made tools and code templates
- ✦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
- ✦Open hybrid data lakehouse
- ✦Connects data across clouds and on-prem
- ✦Governance, lineage and access controls
- ✦Business-context enrichment
- ✦AI-ready data for analytics and models
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Data for generative AI
- →Lead generation
- →Market research
- →Sentiment analysis
- →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
- →Unifying fragmented enterprise data
- →Governing data for AI workloads
- →Moving AI pilots to production
- →Powering analytics with trusted data