ENGINEERING BLOG
Technical research and engineering insights from the team building the operating system for responsible AI operations.
121 articles · Published by MARIA OS
How to build a self-improving governance OS through six mathematical research programs, four agent teams, and a Research Universe architecture
Judgment is harder to scale than execution, especially in high-stakes decision environments. This paper presents six research frontiers — from hierarchical speculative pipelines to constrained reinforcement learning — for extending MARIA OS from product operations into governed decision science. We formalize each frontier with mathematical models, design four agent-human hybrid research teams, and introduce the Research Universe: a governance structure where each experiment is evaluated through the same fail-closed gates it studies.
Using spectral methods on evidence correlation matrices to identify inconsistencies, fabrication patterns, and systemic fraud signals
Traditional audit systems often rely on rule-based checks and statistical sampling, which can under-detect coordinated fabrication patterns. This paper introduces Evidence Coherence Spectral Analysis, a framework that treats evidence sets as vector spaces, builds correlation matrices from evidence attributes, and applies eigendecomposition to identify anomalous spectral gaps associated with inconsistency or fabrication risk. We define a coherence score, relate it to false-discovery behavior, and describe integration with MARIA OS Evidence Bundles. In controlled financial-statement audit experiments, spectral analysis detected 94.7% of fabricated evidence sets while maintaining a false-positive rate below 2.3%, with streaming support for near-real-time analysis.
Five axioms, four pillar equations, and five theorems that transform organizational judgment into executable decision systems
Decision Intelligence Theory formalizes decision-making as a control system, integrating evidence, conflict, responsibility, execution, and learning to reduce false allowances while improving organizational completion rates. This capstone article presents a unified mathematical framework — five axioms, four pillar equations, and five theorems — with proofs, implementation mappings, and cross-industry validation across finance, healthcare, legal, and manufacturing.
Defining audit termination conditions through MAX constraints and probability thresholds to minimize False Allow Rate
Every audit faces the same question: when is evidence sufficient to stop? Stopping too early can allow defects to escape into production, while stopping too late consumes budget and attention with diminishing returns. This paper formalizes audit stopping criteria as a constrained optimization problem, derives solutions under MAX constraints and sequential probability ratio testing, and describes integration with the MARIA OS Fail-Closed Gate Engine. In evaluated SOX workloads, the approach reported a False Allow Rate below 0.3%.
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Complete list of all 121 published articles. EN / JA bilingual index.
121 articles
All articles reviewed and approved by the MARIA OS Editorial Pipeline.
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