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RabbitHawk

Why RabbitHawk

Decision science, built into the product

Researchers in probabilistic forecasting, optimization and machine learning work alongside the engineers building RabbitHawk.

  • Uncertainty modelling
  • Constraint optimization
  • Context intelligence
  • Governed evaluation

Measured client outcomes

Multinational apparel retailer

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Reduction in new inventory
52%Reduction in new inventoryobserved sales revenue maintained during the evaluated period
Reduction in MASE
96%Reduction in MASEversus saved legacy forecasts at style × colour × store × brand
Reduction in manual workload
90%Reduction in manual workloadfrom weeks to hours
Decision cycle
3 wks → 1 dayDecision cyclefrom debate to coordinated action

What the product preserves

Scientific discipline in the operating workflow

Uncertainty stays explicit

Contextual beliefs, predictive distributions and information cutoffs remain visible from evidence through evaluation.

Optimization respects the operation

Recommendations account for budgets, capacity, lead times, service requirements and the costs of changing a plan.

Context becomes model input

People and connected agents contribute evidence. RabbitHawk forms a probabilistic belief before a forecasting model recomputes affected demand.

Every version can be evaluated

Reference forecasts, contextual candidates, human belief amendments and approved versions remain available when outcomes arrive.

Measured client outcomes

A multinational retailer engagement reduced a three-week planning cycle to one day, with the comparison basis retained in the case study.

Specialists stay involved

RabbitHawk combines software with forecasting, operations-research, validation and implementation expertise.

One connected method

Forecast, decide and learn without hiding uncertainty

The same governed objects connect evidence, uncertain beliefs, possible futures, decisions and outcomes.

01

Probabilistic forecasting

Forecast distributions remain available to the decisions that depend on them.

02

Contextual evidence

Human knowledge and agent-detected signals become reviewed, uncertain model inputs.

03

Decision optimization

Actions are evaluated against objectives, constraints and the selected forecast distribution.

Bring us the decision that is difficult to improve

We will identify whether the right starting point is forecasting, optimization, Forecast Interventions or specialist work.

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