Tested. Proven. Trusted.

At Haystax, our seasoned team of data scientists, engineers and physicists has over 75 combined years of expertise in applied knowledge representation and reasoning, system and software complexity management, abstraction, model composition, application-specific language definition, formal ontology development, hybrid-paradigm framework and applications development, computational statistics, Bayesian inference, data integration to support decision-making, natural language processing and geospatial science and applications. They have collectively developed and implemented computer models of complex knowledge domains in the fields of human behavior, military intelligence data fusion, military engineering, military command & control, intelligence preparation of the battlefield, geospatial information, human health surveillance and terrorism and cybersecurity risk management.

Peer Reviewed
Scientific Papers

Learn more about our probabilistic model-based approach:

  • Automating the Construction of Indicator Hypothesis Bayesian Networks from Qualitative Specifications
  • Target Beliefs for SME-Oriented, Bayesian Network-Based Modeling
  • Processing Events in Probabilistic Risk Assessment
  • Probabilistic Argument Maps for Intelligence Analysis: Completed Capabilities
  • Probabilistic Argument Maps for Intelligence Analysis: Capabilities Underway
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Join the conversation

Haystax sponsors the Washington DC area’s Bayesian Data Science DC Meetup.com Group. This group hosts lively discussions focused on cybersecurity topics (e.g., artificial intelligence, model science, insider threat analytics, etc.) so that we may all share knowledge and benefit. To find out more or sign up for the next sessin, click the button below.


Read our latest paper

Haystax data scientists continuously push the boundaries of artificial intelligence-driven  analytics. We have received approval to present our latest research paper, Data Value Analysis for Predicting Insider Threat Risk using a Bayesian Inference Network, at a conference in January 2020. Get your own sneak preview. Click the button below!