Multi-Agent Orchestration — Manufacturing Operations Intelligence
Background
A manufacturing company in United States operated across 3 manufacturing plants and 2 distribution centres. Their enterprise stack had grown organically over 15 years: SAP ERP, a legacy MES (Manufacturing Execution System), Salesforce for sales and orders, a separate WMS (Warehouse Management System), and a homegrown quality tracking tool. Each system had its own team, its own data, and its own reporting cadence.
Leadership had invested heavily in these systems. Replacing them was off the table. But the lack of intelligence across them was costing real money: production delays caused by demand signal lag, inventory mismatch between plants, and quality escapes that were not caught until they reached the customer.
Problem
- Demand-production lag Sales order signals in Salesforce took 2 to 4 days to translate into adjusted production schedules in SAP and MES. By the time schedules updated, demand had already shifted
- Inventory blind spots No single view of inventory across all 5 facilities. Plant managers made decisions on stale data, leading to overstock in one location and shortage in another
- Quality escape leakage Quality defect data lived in the homegrown tool and was reviewed weekly in a manual report. Issues compounded for days before anyone acted
- Cross-system fragmentation Answering "Can we fulfil this order by Thursday?" required a human to manually check Salesforce, SAP, WMS, and MES and reconcile the answers
No system talked to another in real time. Every cross-functional decision required a human coordinator acting as the integration layer.
Implementation note
Both the legacy MES and the homegrown quality tracking tool had no documented APIs. Amorisoft's integration team built lightweight adapter services from scratch using reverse-engineered internal endpoints, adding 3 weeks to the integration phase and requiring sign-off from the client's IT security team before the adapters could be deployed in the production environment. This is a common pattern with organic enterprise stacks built over many years, and is one reason Amorisoft's scoping process now includes a mandatory integration audit before timelines are confirmed.
Solution
Amorisoft designed and deployed a Multi-Agent Orchestration layer that sat above the client's existing systems, connecting to each via APIs and webhooks without modifying or replacing any underlying platform.
The agent network consisted of six specialised agents coordinated by a central Orchestrator:
- Demand Signal Agent Monitored Salesforce for new orders, order modifications, and pipeline changes in real time; translated commercial signals into production demand deltas
- Production Scheduling Agent Interfaced with SAP and MES to evaluate current production schedules against incoming demand signals; proposed schedule adjustments within configured parameters
- Inventory Balancing Agent Maintained a real-time unified inventory view across all 5 facilities via WMS integration; identified imbalances and triggered inter-facility transfer recommendations
- Quality Watchdog Agent Polled the quality tracking system every 15 minutes; applied statistical process control logic to detect emerging defect patterns before they crossed threshold; auto-escalated to plant quality leads with contextual data
- Fulfillment Feasibility Agent Answered the "can we ship by X?" question in under 30 seconds by orchestrating live queries across Salesforce, SAP, WMS, and MES simultaneously
- Central Orchestrator Coordinated agent activity, managed conflict resolution, and surfaced a unified operations intelligence feed for leadership
All agents operated within the client's existing AWS infrastructure. No data left their environment.