Designing Intelligent
Decision Systems
for Energy, Industry & Enterprise.
Petroleum Engineer. Decision Systems Architect. Software Engineer. I build reliable, explainable software for safety-critical operations.
What are poor decisions costing you?
Every strategic decision carries risk. Poor decision quality costs 2–5% of revenue in most industries, and far more in capital-intensive sectors. This calculator combines your company context with public data and AI interpretation to estimate your exposure.
Calibrated against industry benchmarks (CHAOS, McKinsey, IPA, EIA, OECD, Fed studies)
Enriched with SEC EDGAR, FRED, BLS, GDELT, and sanctions data
AI synthesizes the risk picture; deterministic engine computes the estimate
This is not financial VaR. It estimates your annual cost of decision failure: the revenue you are likely losing each year because major strategic and operational decisions are poorly framed, under-supported, or badly executed.
The estimate combines your industry baseline (capital-project overruns, IT failure rates, quality losses, operational-risk losses), your decision-maturity profile, and live public signals (SEC financial health, macro conditions, country risk, news sentiment). Think of it as a decision-quality MRI, not a financial audit.
The more context you share, the tighter the estimate. Only industry and revenue are required; everything else sharpens the calibration.
Pulls live signals from SEC EDGAR, FRED, BLS, GDELT, and World Bank. No AI — pure data fetching.
Reads your context + enriched signals. Returns a risk narrative and small factor nudges (±15% max). Does NOT compute dollars.
Pure math: revenue × industry failure rate × cost multiplier × all context factors = dollar estimate. No AI.
Engineering before aesthetics.
How can complex decisions become more reliable, explainable, and repeatable? The world is becoming increasingly instrumented. Industrial facilities generate more operational data than ever before. Enterprises collect information across every process. Artificial intelligence is advancing at an unprecedented pace. Yet many critical decisions that influence safety, productivity, reliability, and financial performance are still fragmented across disconnected systems, undocumented expertise, and reactive workflows. My work is driven by this simple question. I approach this challenge from two perspectives: practical industrial experience and software systems architecture.
Precision execution across domains.
Software Engineering
9/10
Industrial Systems
10/10
Enterprise Architecture
10/10
Artificial Intelligence
8/10
Data Engineering
8/10
A timeline of operational experience.
PTI
Foundational engineering principles.
Industrial Training
Exposure to large-scale industrial operations.
Indorama Petrochemical
Practical application in safety-critical environments.
Decision Systems
Architecting software for complex operational choices.
Industrial AI
Integrating intelligence into operational workflows.
Energy Research
Applying advanced systems to energy infrastructure.
Future Vision
Designing intelligent platforms for global infrastructure sectors.