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papers/hanzo-ai-cloud/sections/09-provider-marketplace.tex

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\section{Provider Marketplace}
\label{sec:marketplace}
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Hanzo AI Cloud is not a single-operator cloud. It is a marketplace of compute
providers, each staking HANZO tokens as collateral for their service quality
commitments.
\subsection{Stake-Weighted Selection}
Providers register on-chain with:
\begin{itemize}[leftmargin=1.1em]
\item \textbf{Hardware attestation}: Verified GPU inventory (model, VRAM,
count) via TPM-based attestation.
\item \textbf{HANZO stake}: Minimum 10,000 HANZO per GPU. Higher stake
increases scheduling priority.
\item \textbf{SLA declaration}: Committed latency (p99), uptime (monthly),
and throughput (tokens/sec).
\item \textbf{Pricing}: Per-token, per-image, or per-second pricing in
HANZO.
\end{itemize}
The scheduler selects providers using a score function:
\begin{equation}
\text{score}(p) = \alpha \cdot \frac{S_p}{\sum_j S_j} +
\beta \cdot \frac{1}{L_p} + \gamma \cdot \frac{U_p}{T_p} +
\delta \cdot \frac{1}{C_p}
\end{equation}
where $S_p$ is stake, $L_p$ is historical latency, $U_p/T_p$ is uptime ratio,
$C_p$ is price, and $\alpha + \beta + \gamma + \delta = 1$ are
user-configurable weights. Users who prioritize cost set $\delta$ high; users
who prioritize reliability set $\gamma$ high.
\subsection{SLA Enforcement}
SLA violations are detected automatically and enforced on-chain:
\begin{itemize}[leftmargin=1.1em]
\item \textbf{Latency violation}: If measured p99 exceeds declared p99 by
$>$20\% over a 1-hour window, the provider is penalized 0.1\% of stake.
\item \textbf{Uptime violation}: If monthly uptime falls below declared
SLA, the provider is penalized proportionally (up to 5\% of stake per
month).
\item \textbf{Incorrect output}: If a verifier detects an incorrect
inference result (via PoAI spot-checking), the provider is slashed up
to 25\% of stake.
\item \textbf{Compensation}: Slashed HANZO is distributed to the affected
users as compensation, not burned.
\end{itemize}
\subsection{Compute Bidding}
For batch workloads (training, fine-tuning, bulk inference), providers submit
bids in a sealed-bid auction:
\begin{enumerate}[leftmargin=1.4em]
\item The user submits a job specification (model, dataset size, deadline).
\item Providers submit sealed bids (price, estimated completion time).
\item The scheduler selects the bid with the best score (price $\times$
time, weighted by stake and historical performance).
\item Payment is escrowed in HANZO. Released on verified job completion.
\end{enumerate}
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