
Going beyond automation, enabling you to make data-driven resource decisions faster, simpler & more effectively
Multi-Agent Orchestration (MAO) is a new field of AI focused on solving complex planning and scheduling problems across the supply chain. It brings together fleets of assets, whether human-operated, semi-autonomous, or fully autonomous, and coordinates their actions to work efficiently as one system. A MAO engine understands the capabilities of every asset, matches them to the right tasks, and finds the most effective, low-cost way to get the job done while considering real-world factors such as time, capacity, and safety. The result is a smarter, more adaptive operation that reduces waste, improves utilisation, and helps teams respond in real time when conditions change.
As AI systems become increasingly sophisticated, multi-agent orchestration has become essential for maximizing their effectiveness in complex environments. Without orchestration, agents operate in isolation, leading to fragmented systems, duplicated effort, inconsistent results, and errors that undermine scalability, reliability, and the ability to tackle complex tasks.
Accelerates Planning
Can deliver optimal plans in under 1 second
Maximises Resources
Reduces operational costs by up to 70%
Ensures Precision
Decreases errors by 83%, minimising operational risk
Empowers Decisions
Builds confidence through real-time data-driven insights
Adapts Continuously
Responds instantly to changing conditions
* Figures for the MAO sector are changing regularly due to the relatively novel nature of the sector.
"Rather than replacing human expertise, our technology is designed as a human-on-the-loop system, working with people to enhance their capabilities."

Dr Colm Flanagan
Founder & Managing Director @HIROCO
We recently conducted a case study for an Australian government department, using our MAO tech to evaluate the public transport network in a specific city resulting in.
-70%
Lowered total operating costs
35 >12min
Reduced the average trip duration from




