> For the complete documentation index, see [llms.txt](https://docs.bonzai.sh/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bonzai.sh/readme.md). # Welcome to BonzAI BonzAI helps people use AI without giving up ownership of their work. Most AI products ask you to send prompts, files, images, business ideas, and training data to someone else's servers. BonzAI takes the opposite path: chat, generate, capture, train, automate, mint, and earn from your own machine first. ## The Problem BonzAI Solves AI is becoming the new creative and operational layer of the internet, but most users are stuck with a bad tradeoff: * Use powerful cloud tools and give up privacy, control, and upside. * Download a local model and get privacy, but lose the product layer that makes AI work compound over time. That is the real gap: **continuity**. A model can answer a prompt. BonzAI is built around what happens before and after that prompt. It remembers the useful context you captured, keeps the source and metadata attached, turns raw material into datasets, lets those datasets improve future outputs, gives agents and companies a way to act over time, and preserves a path from private work to published assets and rewards. The work does not disappear into a chat box, and it does not have to live on someone else's platform to become useful. BonzAI's moat is the loop: ``` private context -> structured data -> generation -> training -> automation -> ownership -> rewards ``` Local model tools usually stop at inference. BonzAI turns local inference into a private AI operating system where every useful output can become reusable memory, training material, a minted asset, a company deliverable, a companion skill, or a rewardable contribution. | Option | What you get | What is missing | | ------------------- | -------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------ | | Cloud AI apps | Powerful models and polished UX | Privacy, ownership, local control, and direct upside from your work | | Local model runners | Private local inference | Continuity: captured context, reusable datasets, training loops, agents, companies, publishing, and reward routing | | BonzAI | A private AI loop where work can accumulate, improve, ship, and earn | Hardware still matters, so BonzAI supports browser AI, Desktop AI, and provider workflows | ## The Three Products | Product | Plain-English purpose | | ------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **BonzAI Web** | Try BonzAI in the browser, learn what the product does, and get the right download or extension link. | | **BonzAI+** | A browser assistant that can chat about pages, capture text/images, follow videos, generate images, and build datasets from the web. | | **BonzAI Desktop** | The full local AI studio: generate text/images/audio/video/3D, train with datasets, mint assets, run companions, form Zero-Human Companies, and join the provider economy. | ## What You Can Do With BonzAI * Chat privately with local AI. * Generate images, audio, music, video, and 3D scenes. * Capture useful text and images while browsing. * Turn captured material into datasets. * Import datasets into Desktop for training and fine-tuning. * Mint generated content as ownable assets. * Create autonomous AI companions with wallets and onchain identity. * Launch companion and model tokens. * Operate agentic business teams that prepare, execute, review, and remember real work. * Share compute as a provider and earn from service-time rewards. ## Why BONZAI Exists BONZAI is not a paywall for basic generation. If it were only a toll token, it would make BonzAI worse. The token exists because BonzAI is not only an app. It is a way for private AI work to become portable property, reputation, and revenue-bearing infrastructure. When work leaves the private workspace and enters the shared economy, BonzAI uses three signals together: * **Proof of Contribution**: what did this user, dataset, companion, provider, evaluator, or company actually add? * **Staked $BONZAI**: how much committed economic weight does that participant bring? * **Usage and quality**: did the asset actually help people, models, companions, providers, or companies? That combination matters. Contribution alone can recognize useful work, but it does not create durable demand for the token. Staking alone can create demand, but it does not prove anyone made the system better. BonzAI needs both contribution and staking. Together they help answer: * Who made this? * Who captured or curated the data? * Who trained or evaluated it? * Who served the compute? * Who owns the resulting asset? * Who should earn when it is used? Inside BonzAI Desktop, the Ownership Dashboard exposes staking, contribution packs, trained models, minted assets, tokenized models, routes, and registry status. Base contribution ownership is immutable once revenue begins; staked `$BONZAI` adds utility weight and a separate bonus rather than taking royalties from the people whose work was used. That is the larger idea behind BonzAI: private AI that can become ownable, reusable, trusted, and economically meaningful without forcing every prompt through a centralized account system. ## Start Here * New users: [Product Suite](/product-manuals/products.md) * Real examples: [Scenario Map](/everyday-workflows/user-scenarios.md) * Desktop automation: [Agentic Teams for Business](/business-automation/zero-human-company.md) * Token utility: [$BONZAI Utility](/ownership-and-economy/bonzai-utility.md) * Staking architecture: [Staking Architecture](/ownership-and-economy/staking-architecture.md) * Rewards and claims: [Reward Structure](/ownership-and-economy/reward-structure.md) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.bonzai.sh/readme.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.