Decision intelligence technology firm Gurobi Optimization is partnering with global large-scale battery energy storage systems (BESS) Akaysha Energy to help optimise its portfolio.
The global developer and operator of large-scale BESS will seek to enhance forecasting accuracy, operational efficiency, and market optimisation across Akaysha’s growing global portfolio.
Founded in Australia in 2021, Akaysha Energy now has projects across Australia, Japan, the US, and Germany.
Gurobi’s mathematical optimisation technology will seek to enable Akaysha to make faster, data-driven decisions across millions of market variables each day.
CEO of Gurobi Optimization Duke Perrucci says this helps the company improve both long-term revenue forecasting and real-time operational performance ensuring its battery assets deliver optimal returns in a dynamic energy market.
Gurobi’s technology uses advanced mathematics to evaluate millions of possibilities and quickly find the best one – turning complexity into clarity so businesses can move faster and perform better, says Perrucci.
“For Akaysha Energy, that means using decision intelligence to optimise how their battery systems operate in dynamic market conditions, improving forecasting accuracy, refining trading strategies, and ensuring their assets deliver maximum value,” adds Perrucci.
“It’s rewarding to see how our technology can support innovators like Akaysha in accelerating the clean energy transition.”
Intelligent decision-making
Tim O’Sullivan, General Manager, Energy Market Software Development at Akaysha Energy, says optimising a battery energy storage system in a dynamic energy market involves millions of decisions daily.
“Gurobi gives us a robust framework to develop, test, and deploy optimisation models that improve the speed and accuracy of our forecasting and performance assessments,” O’Sullivan says.
Founded in 2008, Gurobi has operations in the Americas, Asia, and Europe. Its decision intelligence technology enables customers to make optimal business decisions in seconds – from workforce scheduling and portfolio optimisation to supply chain design, among others.
Gurobi recently released its 2025 State of Mathematical Optimization Report, highlighting how enterprises are adopting optimisation alongside generative AI (GenAI) and machine learning to solve strategic and operational challenges.
The report shows growing experimentation with GenAI integration and persistent demand for optimization professionals.
Gurobi’s report highlights how mathematical optimisation has long been critical for industries like finance, logistics, and manufacturing. What’s new in 2025 is its intersection with AI.
“While only 6% of organisations currently combine optimization with GenAI, nearly a quarter are actively experimenting, and another 30% are interested but not yet started. Developers are increasingly expected to bridge optimisation engines, ML models, and AI assistants into production-ready pipelines,” the report says.
“The survey shows 41% of respondents expect GenAI to play a significant role in decision-making within two years. That aligns with the rise of agentic AI, or systems that combine reasoning, optimisation, and data-driven actions.”
Write to Adam Orlando at Mining.com.au
Images: Akaysha & Unsplash
