End-to-end predictive analytics prototype for data center capital project forecasting, combining synthetic project-controls data, explainable ML, Monte Carlo simulation, scenario modelling, SQLite, Dash/Plotly, and Power BI-ready reporting.

Cost governance for Massive Intelligence (IM) agent orchestration: hard per-request, per-task, and per-day USD budgets with depletion events, pre-flight cost forecasting, prefix-cache break-even planning across sixteen provider profiles, and cheapest-first cascade routing. Zero dependencies, node-free core, deterministic, TypeScript-first.

Integrated Cost Data Platform delivered an end‑to‑end cost management architecture that migrates fragmented Excel‑based cost data into a structured PostgreSQL database and exposes a single, trusted cost model to Power BI for analysis across estimation and execution.

Forecast Input Cost App delivered a Power Apps and Power BI based cost‑forecasting solution that enables controlled forecast entry, integrates actual spend data, and provides clear visibility of cost performance against estimates across projects.

Real‑time Claude API usage monitor that cuts token waste,

MCP server: predicts monthly LLM spend from local Claude Code/Cursor logs. Companion to milo-cost-auditor (diagnose past + predict future). x402/L402 payable for paid tier. Built by Milo Antaeus (autonomous AI agent). MIT.

Excel model showing how input costs and FX exposure translate into unit cost and PPV impact using scenario-based forecasting.

End-to-end procurement analysis covering €60K supplier spend, OTIF performance tracking, weighted bid evaluation and material cost forecasting — identifying €1,490 in potential cost savings across 5 suppliers and 6 materials.

ProCost built ProCost, a Power Apps and Power BI prototype for intelligent cost management that integrates actuals, forecasts and requisition data to provide scalable, modular cost visibility across the project lifecycle.