Deployed a decentralized swarm of 24 specialized AI agents that dynamically reroute global cargo ships, forecast port congestions, and negotiate customs clearances in real time.
The client suffered millions in demurrage fees due to unexpected port bottlenecks and rigid legacy routing software that could not react to storm systems or geopolitical changes.
We engineered a multi-agent swarm where weather agents, customs agents, and fuel optimization agents collaborate via LangGraph, simulating thousands of maritime routes per second to execute automated schedule adjustments.
Each agent in the network has domain-specific fine-tuned prompts, tools, and validation constraints.
Agents peer-review and verify each other's outputs before publishing final decisions, eliminating hallucinations.
Managed with LangGraph and CrewAI running on Kubernetes for elastic scale across millions of requests.
Swarms dynamically spawn worker sub-agents during traffic surges and consolidate when idle.
JP INFOTECH's multi-agent swarm gave us predictive superpowers. Our logistics operations went from reactive chaos to proactive precision.
Share the constraint you're up against. A principal engineer who worked on systems like this replies within one business day.