Markuss Saule
I am a systems-first analytics builder focused on operational risk, bottlenecks, and decision thresholds in complex organizations.
I build
Business Analytics student at BYU-Idaho building high-consequence analytics for healthcare, market systems, and enterprise operations. My work is designed for environments where tradeoffs matter and decisions carry real cost.
Healthcare is personal to me. Family health challenges shaped how I define impact, and why I care about platform-level systems that improve outcomes at scale.
New Flagship
OWL: Autonomous AI Discovery Daemon
OWL is a local-first Node.js daemon that watches your data sources — email, calendar, GitHub, Slack, Shopify — builds a living world model, and surfaces high-value discoveries when something matters. Desktop app, web dashboard, MCP server, Docker, and CLI.
It combines real-time data ingestion, LLM-powered analysis, cross-source correlation, anomaly detection, and a learning feedback loop into a single system that runs quietly on your machine with zero cloud dependencies.
Operating Doctrine
Selected Outcomes
Featured Projects
Local-first AI daemon with knowledge graph, discovery engine, Electron desktop app, MCP server, and 5 deployment modes.
Research-grade exchange simulation for liquidity stress, flash crashes, venue fragmentation, and fee-aware strategy interaction.
SimPy-based engine with pressure scoring, risk signals, and staffing search for high-load operations.
XGBoost fraud scoring combined with tamper-evident records for trust and auditability.
Model comparison from logistic regression to XGBoost with SHAP explainability and deployment artifacts.
Healthcare operations dashboard with forecasting, decomposition, and capacity visibility.