papers/kai/kai.tex

% Kai: typed decisions under deterministic policy. Results.
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\title{Kai: Typed Decisions under Deterministic Policy}
\author{
    Hanzo AI Research\thanks{Corresponding author: [email protected]} \\
    \textit{Hanzo Industries Inc (Techstars '17)} \\
    San Francisco, California \\
    \texttt{https://hanzo.ai}
}
\date{2026-10-22}

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\begin{document}

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\title{Kai: Typed Decisions under Deterministic Policy\\[0.35em]
{\large Results of a decision model and the policy that authorizes its actions}}
\maketitle

\begin{abstract}
\noindent
Kai is a decision model. A caller states a question, the answers it admits and
the evidence; Kai returns a calibrated probability over exactly those answers:
one label of a choice, a yes or a no, or a level of a score. It writes no text.
A deterministic policy, Nio, holds authority over action: the model recommends,
the policy authorizes, and a model verdict can only make a policy verdict
stricter. Kai serves \op{POST /v1/decisions} at \texttt{api.hanzo.ai} on CPUs,
with answers that agree across CPU families to $2\times10^{-5}$. On a frozen
harness of twelve decision tasks Kai averages 0.857 against 0.780 for Jev, a
hosted decision model, and 0.675 for Laya, an open one, winning seven tasks and
trailing on four. It keeps its accuracy as label sets grow from 4 to 150
options; its long-context release reads facts planted in states of up to
31,000 tokens at 0.73 to 0.80, where a model trained on short states reads at
chance; and on Mind2Web its element accuracy is above the published
Flan-T5-Base and GPT-4 baselines at a cost of \$0.00004 a step. Its typed grounding of action consequences, read once on a
sealed suite of 14,832 scenes, is right on 99.94\% of the scenes it grounds,
and every scene whose harm has no exact count escalates to a person. We report
where Kai trails as plainly: it beats neither Jev nor Clef on a public decision
index, it trails on sealed transfer suites, it catches fewer jailbreaks than Jev
at fewer false alarms, and without the policy it does not weigh the stakes of a
trolley problem.
\end{abstract}

\tableofcontents
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\input{sections/01-introduction}
\input{sections/02-interface}
\input{sections/03-evaluation}
\input{sections/04-results}
\input{sections/05-limits}
\input{sections/06-conclusion}

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\bibliography{references}

\appendix
\input{sections/a1-wire}

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