In this video, we dive into the fascinating world of parallel AI agent orchestration using MonkDB. Learn how to leverage MonkDB’s powerful framework to efficiently manage and coordinate multiple AI agents working together in parallel to tackle complex tasks. We'll cover: What MonkDB is: An introduction to MonkDB and how it enhances AI agent performance. Parallel AI Agents: How to set up and orchestrate multiple AI agents running in parallel. Scalability & Efficiency: How MonkDB can help scale AI systems and improve processing efficiency. Practical Use Cases: Real-world examples of MonkDB in action, from multi-agent systems to collaborative decision-making. By the end of the video, you'll understand how to implement and optimize parallel AI agents within MonkDB, making your AI applications more powerful and efficient. Don’t forget to like, subscribe, and hit the bell icon for more AI-related content!
MonkAgent enables multiple specialised AI agents to work together seamlessly on top of MonkDB’s unified intelligence layer. Each agent whether for ventilation, safety, fleet, energy, maintenance, or compliance—consumes the same real-time data, applies its own domain logic, and coordinates actions with others through a shared policy engine.
This orchestrated approach transforms mine and plant operations from isolated, manual decisions into continuous, collaborative, closed-loop automation. Every agent understands site context, respects safety rules, and acts in sync, creating an autonomous environment that optimises energy, productivity, and risk in real time.
Get the latest insights, tutorials, and updates delivered straight to your inbox.
