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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.

Yes, Decision Node makes visualization a breeze. Simply select the graphic or table you want to feature in your next presentation or publication and download as a PNG or CSV

Decision Node is a state-of-the-art AI-driven decision analysis software that makes rigorous and normative decision modeling easy. Compare alternatives and uncertainties to ensure that you are taking the best action backed by data.

Decision trees stand apart from other analytical or AI models because they make the logic of decision-making explicit and transparent. Instead of operating as a “black box,” a decision tree visually maps out choices, uncertainties, and outcomes in a way that clearly shows how each factor influences the result.

Everyone! We all make decisions on a daily basis that can be improved with a decision analysis framework. Decision Node is especially adept at modeling for complex business, legal, and healthcare problems.

In addition to creating decision trees and identifying optimal decisions based on quantified uncertainties, Decision Node is equipped to model differing risk preferences, influence diagrams, dominance probabilities, principal component analyses, analysis of alternatives, value of information, and sensitivity analyses. The default tree maximizes expected value, but Decision Node is equipped to run minimization, maxi-max, maxi-min, mini-min, and mini-max structures, as well.

Yes, Howard is Decision Node’s AI assistant making it possible to generate, edit, and summarize decision trees from natural language prompts.

Yes, Decision Node comes with several pre-loaded example trees so you can explore the functionality of the software from the second after you first log in.

Yes, contact sales for more information.

Yes, and each saved version lets you capture a snapshot in time, making it easy to compare scenarios, revisit earlier assumptions, and document how your model developed.