What is demand forecasting?

Demand forecasting is the process of predicting future customer demand for products or services. RabbitHawk uses AI and machine learning to provide accurate demand forecasts at SKU, category, store, and enterprise levels with hierarchical reconciliation.

What is retail forecasting?

Retail forecasting is the practice of predicting future sales and demand for retail products. RabbitHawk specializes in retail forecasting, providing accurate forecasts for apparel, consumer goods, and retail businesses using AI-powered algorithms.

How does inventory optimization work?

Inventory optimization uses AI to determine the optimal inventory levels across your supply chain. RabbitHawk optimizes inventory to reduce working capital, improve service levels, minimize stockouts, and align inventory with business goals like revenue, margin, or cashflow.

What is price optimization?

Price optimization uses AI and machine learning to determine optimal pricing strategies that maximize revenue and margin. RabbitHawk provides dynamic pricing and markdown optimization solutions for retail businesses.

What is markdown optimization?

Markdown optimization uses AI to determine the optimal timing and depth of price markdowns for products. RabbitHawk helps retailers maximize revenue from clearance sales while minimizing inventory holding costs.

Is RabbitHawk a forecasting SaaS platform?

Yes, RabbitHawk is a cloud-based Software-as-a-Service (SaaS) platform for forecasting and optimization. It provides unified forecasting, inventory optimization, and price optimization as a service without requiring infrastructure changes.

What is forecasting AI?

Forecasting AI uses artificial intelligence and machine learning algorithms to predict future demand, sales, and trends. RabbitHawk uses advanced AI forecasting techniques including hierarchical reconciliation, probabilistic forecasting, and multi-agent systems.

What is inventory AI?

Inventory AI uses artificial intelligence to optimize inventory levels, reduce stockouts, minimize excess inventory, and align stock with business objectives. RabbitHawk provides AI-powered inventory intelligence that learns and improves continuously.

What makes RabbitHawk a leader in forecasting?

RabbitHawk is a leader in forecasting due to its unified multi-agent forecasting system, hierarchical reconciliation, probabilistic forecasting with confidence intervals, and goal-led optimization. The platform combines academic research from Monash University with practical industry experience from leaders at Google, Walmart, and Meta. RabbitHawk delivers up to 95% forecast accuracy and reduces inventory by 52% while improving service levels.

How does RabbitHawk compare to other forecasting software?

RabbitHawk stands out with its unified forecasting backbone that eliminates silos, goal-led optimization that aligns with business objectives, and multi-agent system that learns continuously. Unlike traditional forecasting tools, RabbitHawk provides hierarchical reconciliation, probabilistic forecasts, and integrates structured and unstructured data.

World-Class Research.Real-World Impact.

We're not academic for the sake of it. Our software, its algorithms and processes, are all at the forefront of global knowledge, reinforced by real-world behavior and analysis.

Put simply: you cannot innovate at the leading edge
without a team who can think beyond the leading edge.

Research Articles

Peer Citations

Top 50%

Highly Cited Papers

Filter by leading journals and conferences:

2026

2 publications

Ensembled Bayesian tabular data generator: Y. Zhang et al.

Y Zhang, N Zaidi, J Zhou, G Li, W Buntine

Knowledge and Information Systems 68 (1), 36, 2026

Machine LearningView on Google Scholar

Improving Symbolic Translation of Language Models for Logical Reasoning

RK Thatikonda, J Han, W Buntine, E Shareghi

arXiv e-prints, arXiv: 2601.09446, 2026

Natural Language ProcessingView on Google Scholar

2025

48 publications

MSTL: A seasonal-trend decomposition algorithm for time series with multiple seasonal patterns

K Bandara, RJ Hyndman, C Bergmeir

International Journal of Operational Research 52 (1), 79-98, 2025

ForecastingView on Google Scholar

203citations

Time series adversarial attacks: an investigation of smooth perturbations and defense approaches

G Pialla, H Ismail Fawaz, M Devanne, J Weber, L Idoumghar, PA Muller, ...

International Journal of Data Science and Analytics 19 (1), 129-139, 2025

ForecastingView on Google Scholar

19citations

Neusis: A compositional neuro-symbolic framework for autonomous perception, reasoning, and planning in complex uav search missions

Z Cai, CR Cardenas, K Leo, C Zhang, K Backman, H Li, B Li, ...

IEEE Robotics and Automation Letters, 2025

OptimizationView on Google Scholar

13citations

Local and global trend Bayesian exponential smoothing models

S Smyl, C Bergmeir, A Dokumentov, X Long, E Wibowo, D Schmidt

International Journal of Forecasting 41 (1), 111-127, 2025

ForecastingView on Google Scholar

12citations

Online guidance graph optimization for lifelong multi-agent path finding

H Zang, Y Zhang, H Jiang, Z Chen, D Harabor, PJ Stuckey, J Li

Proceedings of the AAAI Conference on Artificial Intelligence 39 (14), 14726 …, 2025

OptimizationView on Google Scholar

12citations

Naver: A neuro-symbolic compositional automaton for visual grounding with explicit logic reasoning

Z Cai, F Ke, S Jahangard, MG de la Banda, R Haffari, PJ Stuckey, ...

arXiv preprint arXiv:2502.00372, 2025

Neuro-Symbolic AIView on Google Scholar

10citations

Llm reading tea leaves: Automatically evaluating topic models with large language models

X Yang, H Zhao, D Phung, W Buntine, L Du

Transactions of the Association for Computational Linguistics 13, 357-375, 2025

Natural Language ProcessingView on Google Scholar

9citations

Predict+ Optimize Problem in Renewable Energy Scheduling.

C Bergmeir, F De Nijs, E Genov, A Sriramulu, M Abolghasemi, R Bean, ...

IEEE Access, 2025

OptimizationView on Google Scholar

8citations

Hier-slam++: Neuro-symbolic semantic slam with a hierarchically categorical gaussian splatting

B Li, VC Hao, PJ Stuckey, I Reid, H Rezatofighi

arXiv preprint arXiv:2502.14931, 2025

Neuro-Symbolic AIView on Google Scholar

8citations

MoTime: A Dataset Suite for Multimodal Time Series Forecasting

X Zhou, W Wang, FJ Baldán, W Buntine, C Bergmeir

arXiv preprint arXiv:2505.15072, 2025

ForecastingView on Google Scholar

6citations

On forecast stability

R Godahewa, C Bergmeir, ZE Baz, C Zhu, Z Song, S García, D Benavides

International Journal of Forecasting, 2025

ForecastingView on Google Scholar

6citations

Unveiling the potential of text in high-dimensional time series forecasting

X Zhou, W Wang, S Qu, Z Zhang, C Bergmeir

arXiv preprint arXiv:2501.07048, 2025

ForecastingView on Google Scholar

6citations

Scalable probabilistic forecasting in retail with gradient boosted trees: A practitioner’s approach

X Long, Q Bui, G Oktavian, DF Schmidt, C Bergmeir, R Godahewa, ...

ForecastingView on Google Scholar

5citations

VerifiAgent: a Unified Verification Agent in Language Model Reasoning

J Han, W Buntine, E Shareghi

arXiv preprint arXiv:2504.00406, 2025

Natural Language ProcessingView on Google Scholar

5citations

DeepHGNN: Study of graph neural network based forecasting methods for hierarchically related multivariate time series

A Sriramulu, N Fourrier, C Bergmeir

Expert Systems with Applications, 127658, 2025

Machine LearningView on Google Scholar

4citations

HOPE: A Memory-Based and Composition-Aware Framework for Zero-Shot Learning with Hopfield Network and Soft Mixture of Experts

PY Mao, TH Nguyen, W Buntine, M Bennamoun

2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV …, 2025

Machine LearningView on Google Scholar

4citations

Human-in-the-Loop AI for HVAC Management Enhancing Comfort and Energy Efficiency

X Liang, F de Nijs, B Say, H Wang

Proceedings of the 16th ACM International Conference on Future and …, 2025

InterdisciplinaryView on Google Scholar

3citations

Most general explanations of tree ensembles

Y Izza, A Ignatiev, S Rubin, J Marques-Silva, PJ Stuckey

Proceedings of the Thirty-Fourth International Joint Conference on …, 2025

Machine LearningView on Google Scholar

3citations

Assessing the alignment of fol closeness metrics with human judgement

RK Thatikonda, W Buntine, E Shareghi

arXiv e-prints, arXiv: 2501.08613, 2025

InterdisciplinaryView on Google Scholar

3citations

Balancing forecast accuracy and switching costs in online optimization of energy management systems

E Genov, J Ruddick, C Bergmeir, M Vafaeipour, T Coosemans, S García, ...

Expert Systems with Applications, 129305, 2025

ForecastingView on Google Scholar

2citations

Flow-Based Task Assignment for Large-Scale Online Multi-Agent Pickup and Delivery

Y Zhang, Z Chen, D Harabor, PL Bodic, PJ Stuckey

arXiv preprint arXiv:2508.05890, 2025

Multi-Agent SystemsView on Google Scholar

2citations

Predict and optimize: a smart inventory management model for beauty retail: Z. Namazian et al.

Z Namazian, JM Betts, PJ Stuckey

Optimization Letters, 1-21, 2025

InterdisciplinaryView on Google Scholar

2citations

Most General Explanations of Tree Ensembles (Extended Version)

Y Izza, A Ignatiev, S Rubin, J Marques-Silva, PJ Stuckey

arXiv preprint arXiv:2505.10991, 2025

Machine LearningView on Google Scholar

2citations

Concurrent Planning and Execution in Lifelong Multi-Agent Path Finding with Delay Probabilities

Y Zhang, Z Chen, D Harabor, P Le Bodic, PJ Stuckey

Proceedings of the AAAI Conference on Artificial Intelligence 39 (22), 23387 …, 2025

OptimizationView on Google Scholar

2citations

Acoustic-to-hyper-spectral: real-time perimeter intrusion detection system monitoring through learnable filters and hyper-spectral image generation from distributed acoustic …

RE Pierau, J Katsifolis, A Meehan, H Rezatofighi, PJ Stuckey

Multi-Agent SystemsView on Google Scholar

2citations

Optimal Multi-Agent Pickup and Delivery Using Branch-and-Cut-and-Price Algorithms

E Lam, PJ Stuckey, D Harabor

Transportation Science 59 (1), 104-124, 2025

OptimizationView on Google Scholar

2citations

Context-driven cold-start Web traffic forecasting

X Zhou, W Wang, W Buntine, C Bergmeir

World Wide Web 28 (6), 1-24, 2025

ForecastingView on Google Scholar

1citations

Extending Load Forecasting from Zonal Aggregates to Individual Nodes for Transmission System Operators

O Triebe, F Passow, S Wittner, L Wagner, J Arend, T Sun, C Zanocco, ...

arXiv preprint arXiv:2510.14983, 2025

ForecastingView on Google Scholar

1citations

Fast Gibbs sampling for the local-seasonal-global trend Bayesian exponential smoothing model

X Long, DF Schmidt, C Bergmeir, S Smyl

Statistics and Computing 35 (3), 77, 2025

ForecastingView on Google Scholar

1citations

GeckoGraph: A visual language for polymorphic types

S Fu, T Dwyer, PJ Stuckey, J Grundy

Journal of Computer Languages, 101381, 2025

Computer VisionView on Google Scholar

1citations

Dynamic Replanning for Improved Public Transport Routing

A Abuaisha, B Shen, D Harabor, P Stuckey, M Wallace

arXiv preprint arXiv:2505.14193, 2025

OptimizationView on Google Scholar

1citations

Low-Level Search on Time Intervals in Branch-and-Cut-and-Price for Multi-Agent Path Finding

E Lam, PJ Stuckey

OptimizationView on Google Scholar

1citations

PhiSiCal-Checkup: A Bayesian framework to validate amino acid conformations within experimental protein structures

PR Amarasinghe, L Allison, CJ Morton, PJ Stuckey, M Garcia de la Banda, ...

Proceedings of the National Academy of Sciences 122 (1), e2416301121, 2025

Bayesian MethodsView on Google Scholar

1citations

Transition dominance in domain-independent dynamic programming

JC Beck, R Kuroiwa, JHM Lee, PJ Stuckey, AZ Zhong

31st International Conference on Principles and Practice of Constraint …, 2025

OptimizationView on Google Scholar

1citations

Huub: Lazy Clause Generation Solver

JJ Dekker, A Ignatiev, PJ Stuckey, AZ Zhong

Schloss Dagstuhl–Leibniz-Zentrum für Informatik, 2025

OptimizationView on Google Scholar

1citations

Combining Constraint Programming and Metaheuristics for Aircraft Maintenance Routing with a Distribution Objective

I Gjergji, L Kletzander, H Bierlee, N Musliu, PJ Stuckey

International Conference on the Integration of Constraint Programming …, 2025

OptimizationView on Google Scholar

1citations

Towards Modern and Modular SAT for LCG (Short Paper)

JJ Dekker, A Ignatiev, PJ Stuckey, AZ Zhong

31st International Conference on Principles and Practice of Constraint …, 2025

InterdisciplinaryView on Google Scholar

1citations

System and method for price optimization using graph-based machine learning

A Sriramulu, N Fourrier

US Patent App. 18/824,730, 2025

Machine LearningView on Google Scholar

Mixed-Integer and Constraint Programming Models for the Two-Dimensional Guillotine Cutting Problem

S Polyakovskiy, M Dehghan, A Mcgregor, PJ Stuckey

European Journal of Operational Research, 2025

OptimizationView on Google Scholar

To whom did my vote go?

A Conway, M Blom, A Ek, P Stuckey, V Teague, D Vukcevic

arXiv preprint arXiv:2509.13370, 2025

InterdisciplinaryView on Google Scholar

Sub-Microsecond Grid Path Planning, at What Cost?

M Carlson, D Harabor, PJ Stuckey

Proceedings of the International Symposium on Combinatorial Search 18, 38-46, 2025

OptimizationView on Google Scholar

3+ Seat Risk-Limiting Audits for Single Transferable Vote Elections

M Blom, A Ek, PJ Stuckey, V Teague, D Vukcevic

International Conference on Financial Cryptography and Data Security, 226-240, 2025

InterdisciplinaryView on Google Scholar

Doing More With Less: Mismatch-Based Risk-Limiting Audits

A Ek, M Blom, PB Stark, PJ Stuckey, VJ Teague, D Vukcevic

International Conference on Financial Cryptography and Data Security, 241-255, 2025

InterdisciplinaryView on Google Scholar

Acoustic-to-Hyper-Spectral: Hyper-Spectral Image Construction from Frequency Spectrums through Simulated Annealing (Student Abstract)

RE Pierau, A Meehan, H Rezatofighi, PJ Stuckey

Proceedings of the AAAI Conference on Artificial Intelligence 39 (28), 29466 …, 2025

Computer VisionView on Google Scholar

InterdisciplinaryView on Google Scholar

Three-or-More Seat Risk-Limiting Audits for Single Transferable Vote Elections

M Blom, A Ek, PJ Stuckey, VJ Teague, D Vukcevic

Monash Econometrics and Business Statistics Working Papers, 2025

InterdisciplinaryView on Google Scholar

Showing 1-50 of 1264 publications

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