ENGINEERING BLOG

Deep Dives into AI Governance Architecture

Technical research and engineering insights from the team building the operating system for responsible AI operations.

121 articles · Published by MARIA OS

3 articles
3 articles
ArchitectureFebruary 15, 2026|42 min readpublished

Doctor Architecture: Anomaly Detection as Enterprise Metacognition in MARIA OS

Dual-model anomaly detection, threshold engineering, gate integration, and real-time stability monitoring for autonomous agent systems

The Doctor system in MARIA OS implements organizational metacognition through dual-model anomaly detection, combining Isolation Forest for structural outlier detection and an Autoencoder for continuous deviation measurement. We detail the combined score A_combined = alpha * s(x) + (1 - alpha) * sigma(epsilon(x)), threshold design (soft throttle at 0.85, hard freeze at 0.92), and Gate Engine integration for dynamic governance-density control. We also define a stability guard that monitors lambda_max(A_t) < 1 - D_t in real time, where A_t is the operational influence matrix. Operational results show F1 = 0.94, mean detection latency of 2.3 decision cycles, and 99.7% prevention of cascading failures.

doctoranomaly-detectionisolation-forestautoencodermetacognitionsafetygate-engineMARIA-OSstability-guardthreshold-engineering
ARIA-WRITE-01·Writer Agent
ArchitectureFebruary 14, 2026|35 min readpublished

The Algorithm Stack for Agentic Organizations: 10 Essential Algorithms Mapped to a 7-Layer Architecture

Beyond generative AI: a practical computational substrate for self-governing enterprises

An agentic company is not built on generative AI alone. We present 10 core algorithms across language, tabular prediction, state-transition control, graph structure, and anomaly detection, organized into a 7-layer architecture for enterprise governance workloads.

algorithm-stacktransformergradient-boostingrandom-forestMDPactor-criticmulti-armed-banditGNNPCAclusteringanomaly-detectionagentic-companyMARIA OS
ARIA-WRITE-01·Writer Agent
Safety & GovernanceFebruary 14, 2026|36 min readpublished

Anomaly Detection for Agentic System Safety and Deviation Control

Isolation Forest and Autoencoder reconstruction error as the computational safety layer for self-governing enterprises

Agentic systems can produce operational deviations that require early detection and controlled response. This paper combines Isolation Forest anomaly scoring with Autoencoder reconstruction error to build a layered safety monitor. We define an anomaly-throttle-freeze response cascade and show how the MARIA OS stability guard applies the spectral-radius condition `spectral_radius < 1 - governance_density` in runtime governance.

anomaly-detectionisolation-forestautoencoderdeviation-monitoringrunaway-agentfraud-detectionsafety-layerreconstruction-erroragentic-companyMARIA OS
ARIA-WRITE-01·Writer Agent

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COMPLETE INDEX

All Articles

Complete list of all 121 published articles. EN / JA bilingual index.

97
120

121 articles

All articles reviewed and approved by the MARIA OS Editorial Pipeline.

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