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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
No-code AI platform using multi-agent 'employees' to research, build, deploy and market full-stack apps from a prompt.
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
No public pricing
Free trial available
No public pricing
Free trial available
- ✦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)
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦Multi-agent AI team (PM, engineer, analyst, etc.)
- ✦Chat-to-build full-stack apps
- ✦Built-in backend: auth, database, Stripe
- ✦SEO and ads agents
- ✦Race Mode across multiple models
- ✦Code export and GitHub sync
- ✦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
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Build SaaS and e-commerce apps
- →Launch MVPs in minutes
- →Add payments and user login
- →Drive SEO and ad growth
- →Export code and self-host
- →Unifying fragmented enterprise data
- →Governing data for AI workloads
- →Moving AI pilots to production
- →Powering analytics with trusted data