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\section{Introduction}
\label{sec:intro}
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Every major AI cloud platform operates on the same trust model: the user sends
plaintext data to the provider, the provider runs a model on it, the provider
returns a plaintext result. The provider sees everything. The provider's
privacy policy is the only barrier between the user's data and the provider's
training pipeline, the provider's employees, the provider's government
subpoenas, and the provider's security breaches.
This is not a theoretical concern. OpenAI's data retention policy permits
logging all API inputs for 30 days~\cite{openaiapi}. Anthropic retains inputs
for safety evaluation. Replicate processes inputs on shared GPU instances with
no hardware isolation between tenants. The user has no cryptographic guarantee
that their prompt---containing patient records, financial models, legal
strategy, classified intelligence---is not stored, read, or reused.
Hanzo AI Cloud solves this problem at the architectural level, not the policy
level. The system is designed so that the provider \emph{cannot} see the
user's data, not that the provider \emph{promises} not to.
\subsection{Contributions}
\begin{enumerate}[leftmargin=1.4em]
\item Confidential inference via CKKS fully homomorphic encryption with
threshold decryption (\S\ref{sec:fhe}).
\item Agent hosting with capsule isolation: vault, DID, capabilities,
budget, and private memory (\S\ref{sec:agents}).
\item Model serving with verifiable inference receipts anchored to the
Lux A-Chain (\S\ref{sec:serving}).
\item Hanzo Candle: a Rust ML framework with GPU acceleration integrated
into Base Functions (\S\ref{sec:candle}).
\item Jin architecture: unified multimodal inference across vision,
language, and audio (\S\ref{sec:jin}).
\item Edge inference: local models on mobile/IoT with CRDT result sync
(\S\ref{sec:edge}).
\item Provider marketplace with stake-weighted selection and on-chain SLA
enforcement (\S\ref{sec:marketplace}).
\end{enumerate}
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