Multiple specialized agents share context, trigger each other, and execute complex workflows no single system handles.
Every action logged. Every decision explainable.
Agents communicate via pub/sub. Dependents react in milliseconds.
Chain agents: Order → Credit → Carrier → Track → Invoice.
Confidence thresholds and human-in-the-loop gates at any step.
Real-time monitoring: throughput, errors, latency, SLA. Full audit.
Unified event bus. No data silos between agent workflows.
Visual drag-and-drop for multi-agent automation.
Granular permissions per agent per workflow.
Throughput, errors, latency, resolution quality, SLA.
TypeScript SDK with templates, testing, CI/CD for custom agents.
Complete log. SOC 2, GDPR, CCPA compliant.
Planning → carrier → tracking → exception → invoice automated.
Rerouting triggers Email AI + CRM + Orchestrator simultaneously.
4 agents coordinate customs, compliance, carrier, notification.
Answers from our implementation team.
It is Debales’ orchestration layer where specialized agents (email, reroute, load plan, fleet, CRM, orchestrator, and your custom agents) share context over an event bus so one trigger—like a late pickup—can fan out to every system that must react.
They publish domain events (for example, “shipment.exception.opened”) and subscribe to the ones they care about. That keeps latency low—often tens of milliseconds between publish and handler—and avoids custom spaghetti between every pair of services.
Yes. Teams use the TypeScript SDK with starter templates, contract tests, and CI hooks so new agents behave like first-class citizens: same auth, telemetry, retries, and release gates as the pre-built agents.
Each workflow step can require approval, a confidence floor, or a role-based gate. Operations can pause automation for a lane or customer, override a decision, and resume when ready.
The bus applies retries with backoff, dead-letter queues for inspection, and circuit breakers so a flaky partner does not stall unrelated workflows. Dashboards show which events are waiting and why.
See Multi-Agent running on your actual freight data.
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