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Turns Git commits and PRs into AI-summarized daily or weekly reports delivered to Slack or email, no source access.
Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
IBM's open, hybrid data lakehouse that connects, governs and optimizes enterprise data to make it AI-ready across clouds and on-premises.
Free practical deep-learning courses, the fastai library and a book that make state-of-the-art AI accessible to coders.
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
Free trial available
No public pricing
- ✦AI-summarized commit and PR reports
- ✦Daily and weekly scheduled digests
- ✦Slack and email delivery
- ✦One-click OAuth or webhook setup
- ✦GitHub, GitLab and Bitbucket support
- ✦Templates for standups and reports
- ✦Natural-language to Git command suggestions
- ✦AI-driven command matching
- ✦Copy-ready command output
- ✦Git guides and reference
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦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
- ✦Free deep learning courses
- ✦fastai library for PyTorch
- ✦nbdev development tool
- ✦Practical Deep Learning book
- ✦Blog on AI, ethics and technical topics
- →Keep stakeholders updated on what shipped
- →Replace manual status updates and standups
- →Give teams visibility into Git activity
- →Find the correct Git command quickly
- →Learn Git syntax by describing a goal
- →Avoid memorizing Git flags
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Unifying fragmented enterprise data
- →Governing data for AI workloads
- →Moving AI pilots to production
- →Powering analytics with trusted data
- →Learning deep learning as a coder
- →Building models with the fastai library
- →Following AI research and ethics writing