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RabbitHawk

Research & Decision Science

Where forecasting research becomes operational decision infrastructure

RabbitHawk is built on peer-reviewed work in probabilistic forecasting, hierarchical reconciliation, optimization and applied AI, translated into systems that improve real decisions under real constraints.

Dr Christoph Bergmeir
Dr Peter Stuckey
Dr Wray Buntine
Dr Abishek Sriramulu
Dr Frits de Nijs
Meet the researchers
publications
1,181publications
citations
53,485citations
highly cited papers
Top 1%highly cited papers

Scientific foundations

Methods proven in the literature, applied in production

Our team’s research is recognized at the field’s leading venues and used at scale by major organizations. We bring that rigor to enterprise planning, but judge every method by whether it improves decisions in practical settings.

Research → product

  • Hierarchical forecasting

    Local plans do not add up to executive targets

    Reconciled forecasts across every level

  • Probabilistic forecasting

    Point forecasts hide risk

    Full predictive distributions, intervals and scenario ranges

  • Optimization

    Forecasts do not tell teams what to do

    Constraint-aware recommendations

  • Agentic AI

    Context is trapped in emails and notes

    Context ingestion and decision agents

  • Human-in-the-loop AI

    Automation without trust creates resistance

    Approval, override and audit trails

  • Alignment science

    Teams optimize against conflicting goals

    90North alignment and goal clarity

Selected publications

The full peer-reviewed database: search by title, author, venue, category or year.

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Learn the science behind the engine

“Forecasting for Data Scientists”, a free 30-chapter video course by co-founder Dr Christoph Bergmeir, from fundamentals to advanced deep learning.

Explore the course
Research & Decision Science | RabbitHawk