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AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Free practical deep-learning courses, the fastai library and a book that make state-of-the-art AI accessible to coders.
Open-source AI search and vector database platform for building large-scale search, RAG, and recommendation systems.
No public pricing
No public pricing
No public pricing
No public pricing
Free trial available
- ✦Chat-to-app and website generation
- ✦Real-time prototype building
- ✦One-click deploy and hosting
- ✦Templates to start projects
- ✦Credit-based building with shared workspaces
- ✦You own your code and data
- ✦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
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Free deep learning courses
- ✦fastai library for PyTorch
- ✦nbdev development tool
- ✦Practical Deep Learning book
- ✦Blog on AI, ethics and technical topics
- ✦Combined vector, text, and structured search
- ✦Distributed machine-learned ranking at query time
- ✦Streaming search mode for cost-efficient personal/private data
- ✦Support for retrieval-augmented generation pipelines
- ✦Continuous deployment and automated scaling
- ✦Open-source core with a managed cloud option
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →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
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Learning deep learning as a coder
- →Building models with the fastai library
- →Following AI research and ethics writing
- →Building large-scale enterprise search engines
- →Powering RAG pipelines that need strong retrieval relevance
- →Building recommendation and ad-targeting systems
- →Search over personal/private data at lower indexing cost