Research Management and Scenario Modeling

The BPN Platform integrates “Research Management” and “Scenario Modeling,” making it practical to Quantify Stories, starting by organizing data, research, and qualitative insight and ending with probabilistic scenarios based on logic rather than random Monte Carlo simulation.

We drive everything to integrated financial statements and produce interactive reporting so you can clearly see the upsides and downsides you are modeling.

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Logical Graphs
and Probabilistic Graphs

Thanks to 10 years of R&D funded by National Science Foundation grants and private investment, BPN produced a patented architecture that integrates two kinds of graphical models from separate fields of artificial intelligence.

Logical Graphical Model

Logical Graphical Models infer some qualitative relationships (the dotted line) from others.

Our patented architecture makes it practical to use a Logical Graphical Model to organize stories about issues more scalably than with folders and tags and to translate them into a Probabilistic Graphical Model that produces many scenarios without writing stories for all of them. With this insight, leaders can make better decisions.

Probabilistic Graphical Model

Probabilistic Graphical Models infer odds of scenarios for some Issues (the white bars) from scenarios for some other Issues (the black bars) and the conditionality between them (the scatter plots).

In The Cloud

Our innovative integration of both Logical and Probabilistic Graphical Models runs in the cloud on a standards-compliant technology stack, with or without integration with the existing models in your Excel files, and integrates with visualization and reporting software like Tableau.


The Bullet Point Network Platform makes it practical for investors and portfolio companies to quantify their stories, driving strategic decisions with data science about not only the past, but also the future.

Schedule demo? Questions?
Contact us today.

We’d love to show you the power of BPN’s graph technology and experienced research team.