Howard (AI)

Natural-Language Decision Modeling — From Prompt To Optimal Choice

Howard turns plain-English problem statements into complete decision models—decisions, uncertainties, and value nodes—then runs sensitivity, stochastic dominance, and value-of-information analyses with auditable citations.

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Prompt

How Howard Works

A guided path from idea to analyzed decision.

1. Describe

State the decision, objectives, constraints, and context in natural language with no template required.

2. Structure

Howard drafts the decision tree: decision nodes, relevant uncertainties, value nodes, and initial priors.

3. Refine

Iterate with prompts or the visual editor; import data; adjust distributions, utilities, and dependencies.

4. Analyze

Identify the unambiguous optimal alternative, then run sensitivity, value of information, and stochastic dominance analyses.

5. Communicate

Generate a comprehensive analytical report, including cited sources. Generate a script to explain the optimal alternative to others

What Makes Howard Different

Decision-analysis native. Al-accelerated. Auditor-friendly.

Natural-language model building

Construct decision trees with ease by prompting Howard in simple written word. Let Howard take care of the rest.

Citations and provenance

Howard will gather data and make citations for you, giving you peace of mind in your decision trees.

Summaries

Generate smart, executive summaries of your tree in seconds using Howard.

Prompt suggestions

Unsure how to start? Decision Node makes using Howard easy with suggested prompts to help you generate a powerful decision tree with ease.

Why Howard?

Howard honors Ron Howard (Stanford) and Howard Raiffa (Harvard), widely credited with founding modern decision analysis. Their emphasis on clarity, structure, and value-focused thinking guides our design: AI accelerates modeling, while decision analysis foundations ensure traceable, high-quality choices.

Stochastic dominance identifies dominated alternative
Tornado and threshold analyses reveal key model drivers
Value of information measures the value of acquiring more data.
Comprehensive AI-generated reports include sources and citations.

Ron Howard

Howard Raiffa

Manual modeling still welcome

Prefer hand-crafted trees? Decision Node’s visual editor remains first-class. Howard simply removes the blank-page barrier and accelerates expert workflows.

Time to first model:

< 5 min

Distribution templates:

20+

Built-in analyses

VOI, SD, Sens.

Decision Model export formats:

PNG, PDF, SVG

Frequently Asked Questions

What can Howard help me with?
Howard is designed to build, edit, and summarize trees with simple inputs from written language. Put him to the test and describe the tree of your dreams in as many or as few words as you like.
Do I need any technical experience to use Howard?
No, Howard makes decision analysis easy with Natural Language Decision Modeling. Simply enter a prompt and AI-powered Howard will create, edit, and summarize your tree allowing you to extract maximum value out of your analysis.
Can Howard provide sources and citations?
Yes, Howard will produce sources and citations allowing you to defend the contents of your tree in the boardroom or the classroom.
Do I need extensive computing power to use Howard?
No, Howard works with you as long as you are connected to the internet. There is no special hardware or software requirement for the user.

Stop The Guesswork.
Decide With Clarity.

Decide smarter and act faster with AI-powered decision modeling.

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