About

Built To Make Better Decisions Possible

Decision Node was created by a team of engineers, decision analysts, and AI specialists who recognized a gap in the decision analysis landscape.

Our Mission

At Decision Node, we believe that better decisions shape better futures. Every strategic choice whether in business, policy, or personal life involves uncertainty, tradeoffs, and complexity. Our mission is to provide a tool that transforms that complexity into clarity, enabling people to act with confidence.

What We Do

Decision Node is a next-generation decision analysis platform designed to:

Model Complex Choices

Build intuitive graphical decision trees with decision, chance, and value nodes.

Reveal What Matters Most

Identify key drivers through sensitivity analysis, principal component analysis, and value-of-information calculations.

Quantify Uncertainty

Run Monte Carlo simulations to understand probabilities, dominance, and risk profiles.

Explain Decisions Clearly

Our AI Assist doesn’t just analyze, it interprets results in plain language, highlighting tradeoffs and hidden insights.

01.

Clarity in Complexity

Turn uncertainty into structured, visual models.

Reveal What Matters Most

Identify key drivers through sensitivity analysis, principal component analysis, and value-of-information calculations.

Reveal What Matters Most

Identify key drivers through sensitivity analysis, principal component analysis, and value-of-information calculations.

Why Decision Node?

Most decision-making tools stop at numbers. Decision Node goes further:

Clarity in Complexity

Turn uncertainty into structured, visual models.

Insight Beyond the Obvious

Understand not just which option is best, but why.

AI-Powered Analysis

Get expert-level interpretation instantly.

Practical Applications

From mergers and acquisitions to project planning, risk management, healthcare, and public policy—Decision Node adapts to any high-stakes decision.

Our Story

Decision Node was created by a team of engineers, decision analysts, and AI specialists who recognized a gap in the decision analysis landscape. Traditional tools are outdated and intimidating; spreadsheets are limited in their ability to fully capture decision models while other decision analysis platforms are overly complex. We set out to design a platform that combines analytical rigor, intuitive design, and AI-powered interpretation—making decision science accessible to anyone facing complex choices.

Core Team Members

Richard Kim, Ph.D

Chief Engineer

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Giovanni Malloy, Ph.D

Chief Data Scientist

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Giovanni Malloy

Chief Data Scientist

Giovanni has expertise in transforming data into actionable decisions. His past work includes the use of artificial intelligence, economic analysis, and mathematical modeling to provide effective and actionable decision recommendations for partners in health, energy, national security, and entertainment.. Giovanni has a B.S. in Industrial Engineering from Purdue University and a Ph.D. in Management Science & Engineering from Stanford University. Giovanni has spent many years immersed in decision analysis, and has used its methods in health policy analysis, risk analysis, and economic analysis. Giovanni has taught graduate courses in decision analysis at Stanford University.

Richard Kim

Chief Engineer

Richard Kim has extensive experience in risk analysis of complex engineered systems. In addition, he has experience working as a space systems engineer for the United States Air Force where he led the development of an advanced command and control system for the next generation space protection infrastructure for U.S. space forces. Richard Kim has a B.S. in Mathematics from the University of California, Los Angeles; an M.B.A. from California State University, Long Beach; an M.S. in Systems Engineering from the Naval Postgraduate School; and a Ph.D. in Management Science and Engineering from Stanford University. During his studies, one of Richard’s doctoral advisors was Professor Ron Howard, the founder of decision analysis and the namesake of Howard, the AI assistant within Decision Node. Richard teaches decision analysis at Stanford University.