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110 lines
3.8 KiB
TeX
110 lines
3.8 KiB
TeX
% Hanzo AI Cloud: Confidential Inference, Agent Hosting, and Model Serving
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\documentclass[11pt]{article}
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\usepackage{../shared/hanzocover}
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\usepackage{amsmath, amssymb, amsthm}
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\usepackage{mathtools}
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\usepackage{bm}
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\usepackage{graphicx}
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\usepackage{booktabs}
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\usepackage{hyperref}
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\usepackage{enumitem}
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\usepackage{algorithm}
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\usepackage{algpseudocode}
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\usepackage{xcolor}
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\usepackage{float}
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\usepackage{multirow}
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\usepackage{listings}
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\input{../shared/lstlang}
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\usepackage{tikz}
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\usetikzlibrary{shapes,arrows,positioning,fit}
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\usepackage{pgfplots}
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\pgfplotsset{compat=1.18}
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\hypersetup{colorlinks=true,linkcolor=black,citecolor=blue,urlcolor=blue}
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\definecolor{codegreen}{rgb}{0,0.6,0}
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\definecolor{codegray}{rgb}{0.5,0.5,0.5}
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\definecolor{codepurple}{rgb}{0.58,0,0.82}
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\definecolor{backcolour}{rgb}{0.95,0.95,0.92}
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\lstdefinestyle{mystyle}{
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backgroundcolor=\color{backcolour},
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commentstyle=\color{codegreen},
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keywordstyle=\color{codepurple},
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numberstyle=\tiny\color{codegray},
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stringstyle=\color{codegreen},
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basicstyle=\ttfamily\footnotesize,
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breakatwhitespace=false,
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breaklines=true,
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captionpos=b,
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keepspaces=true,
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numbers=left,
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numbersep=5pt,
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showspaces=false,
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showstringspaces=false,
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showtabs=false,
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tabsize=2
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}
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\lstset{style=mystyle}
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\newtheorem{theorem}{Theorem}
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\newtheorem{definition}{Definition}
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\title{HANZO AI CLOUD\\[0.3em]
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{\large Confidential Inference, Agent Hosting, and\\Model Serving on Sovereign Infrastructure}}
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\author{
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Hanzo AI Research \\
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\textit{Hanzo Industries Inc (Techstars '17)} \\
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\texttt{[email protected]}
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}
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\date{March 2026}
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\begin{document}
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\hanzocoverpage
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% ============================================================================
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% ABSTRACT
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% ============================================================================
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\begin{abstract}
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We present Hanzo AI Cloud, an infrastructure layer for AI workloads where the
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provider never sees the user's data. Current AI cloud platforms (OpenAI,
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Anthropic, Replicate, Together) require users to transmit plaintext prompts,
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receive plaintext completions, and trust the provider not to log, train on, or
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leak their inputs. This trust model is incompatible with regulated industries
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(healthcare, finance, defense) and with any user who values privacy as a
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technical guarantee rather than a policy promise.
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Hanzo AI Cloud eliminates this trust requirement through three mechanisms:
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(i)~confidential inference via CKKS fully homomorphic encryption, where inputs
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are encrypted client-side, evaluated homomorphically on the provider's GPUs,
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and decrypted only by the client; (ii)~agent hosting with capsule isolation,
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where each agent receives a private vault, a decentralized identifier, a
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capability budget, and encrypted memory that no other agent or the platform
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can access; and (iii)~model serving with verifiable attestation, where every
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inference result is accompanied by a cryptographic receipt anchored to the Lux
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A-Chain, proving which model produced it, on what hardware, at what time.
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We describe the system architecture, the FHE inference pipeline, the agent
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capsule model, the model registry, Hanzo Candle (the Rust ML framework
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powering GPU inference), the Jin multimodal architecture, edge inference for
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mobile and IoT devices, and the provider marketplace with stake-weighted
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selection and SLA enforcement.
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\end{abstract}
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% ============================================================================
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\input{sections/01-introduction}
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\input{sections/02-the-ai-cloud-problem}
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\input{sections/03-confidential-inference}
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\input{sections/04-agent-hosting}
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\input{sections/05-model-serving}
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\input{sections/06-hanzo-candle}
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\input{sections/07-jin-architecture}
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\input{sections/08-edge-inference}
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\input{sections/09-provider-marketplace}
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\input{sections/10-comparison-to-existing-platforms}
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\input{sections/99-conclusion}
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\end{document}
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