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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.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Big-data and AI platform (Foundry, Gotham, AIP) for integrating and analyzing large datasets across government and enterprise.
No public pricing
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
No public pricing
- ✦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
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦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
- ✦Gotham platform for government/defense
- ✦Foundry enterprise data integration
- ✦AIP for operational AI and LLMs
- ✦Large-scale data integration and modeling
- ✦Analytics and decision support
- ✦Data security and governance
- →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
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Government, defense and intelligence analytics
- →Enterprise data integration
- →Operational decision-making
- →Deploying AI on proprietary data