When you build for ten customers, none of them should ever see another's data.
Contract manufacturing runs on multi-customer tenancy, shop-floor exceptions, yield variance you cannot let leak across walls, and RMA flow that requires PLM context. OpsATC.AI is built for that operating model from day one — architectural tenant isolation across every layer of the stack, MES integration via MCP, yield analytics on a per-tenant graph, and The Captain briefed on each customer's PLM revision before she opens a ticket.
Architecturally, one customer's view never crosses another's.
If you build for competing customers, tenant isolation is not a feature — it's a contract requirement, a liability boundary, and a sales argument. OpsATC.AI enforces it at every layer from day one.
The five drains every CM operation faces.
In the discovery conversations we've had with contract manufacturers, a recurring pattern keeps surfacing — five drains that come up on nearly every call. The Captain is designed around exactly these.
Multi-customer chaos
Ten customers, ten work orders, ten engineering revisions, ten different definitions of "done." Your shop-floor leads track which customer's spec applies to which lot in spreadsheets and tribal knowledge. The cost of getting it wrong is a CAPA.
MES exception triage
Yield drops on Line 3. Test failures spike on a specific lot. The pattern is in the MES; the root cause may be in PLM (revision change), procurement (component substitution), or the WMS (handling). Today, that's a 90-minute meeting.
RMA without context
A customer returns a unit. The RMA team needs the build record, the inspection results, the firmware version, the supplier-component traceability, and the PLM revision in effect when this unit was built. Today, six tabs and a phone call.
QMS & CAPA cycles
Customer audits, internal CAPAs, supplier non-conformances — the data is in the QMS, but the closed-loop tracking lives in someone's spreadsheet that nobody can find when the auditor arrives.
New-customer ramp
Bringing a new customer onto your floor is months of EDI mapping, item master sync, BOM ingestion, customer-specific work-instruction setup, and quality-spec ingestion. The ramp tax is real margin.
All five run on the same orchestration layer
The Captain doesn't replace your shop-floor leads, your quality team, or your customer-program managers. She compresses the time from signal to decision — across all your customers, with hard tenant boundaries, with audit-grade logs ready for the next ISO audit.
Read · reason · cite · draft. Operator approves.
The Captain reads each customer's live systems via MCP — bound to that tenant's data only — reasons across the BOM, the build record, the yield stream, and the spec, drafts cited recommendations for shop-floor leads, the quality team, and customer-program managers, and stops at the operator. Every commit happens in your existing MES, QMS, or PLM, with the source records cited and the audit log captured. Verified outcomes feed the next round of yield-pattern detection — closed-loop, per tenant.
Workflows built for the multi-customer floor.
Internal Ops · Multi-customer view, one switch
Operations Director sees the consolidated dashboard across all customers, with strategic KPIs and exception ranking. Shop-floor lead switches to the active customer's view in one click — same agent, fully scoped to that customer's data only. Tenant ID enforced at the prompt-construction layer, not just at retrieval.
MES Exception → PLM Cross-Reference
When yield drops or test failures spike, The Captain pulls the relevant MES events, cross-references against the PLM revision history, surfaces any supplier-component changes from procurement, and drafts the engineering-change recommendation with full cited source records.
Service · RMA briefed before triage
RMA tickets land with the build record, the inspection results, the firmware version, the supplier-component lot, and the PLM revision in effect when the unit shipped — all auto-pulled, all cited. The CAPA cycle starts from full context.
Process Intelligence · Yield-pattern detection
The engine is designed to watch the per-tenant yield stream continuously, identify the pattern (lot, line, shift, supplier), quantify the cost (rework, scrap, missed-OTIF risk), and track the intervention closed-loop. The architecture is set up so verified outcomes feed the next round of detection.
Per-persona outcome targets — measured against your baseline.
Design-stage targets, not promised magnitude. The first design-partner pilot is where the delta gets measured against your operator baseline. Below: where The Captain is built to move the needle, by role.
Reason across both stacks in one query
Designed to enable cross-customer-stack reasoning — SAP customer A and Oracle customer B answered in the same query without leaking either's IP into the other's recommendations.
Traces to: Architectural — canonical model
One ranked queue across Coupa, the MES, the WMS
Designed to converge procurement (Coupa/Ariba), MES (Plex/Aegis/Tulip), and WMS (Manhattan) into one impact-ranked exception queue — reviewed and approved in seconds, not minutes.
Traces to: Cross-stack orchestration
Yield drift correlated with customer-side signal
Designed to surface MES first-pass-yield drift correlated with customer-side ERP signal before the next escalation call — the pattern that drove last week's miss is named, not buried.
Traces to: Process Intelligence · cross-stack
Live cross-stack "where is the work?"
Designed to convert the Friday-afternoon spreadsheet rebuild into a live, role-scoped dashboard that reads cross-stack from the canonical model — no glue layer, no reconciliation lag.
Traces to: Hybrid Exec Roll-up equivalent
"We're on track" becomes citable
Designed to make every customer status update a citable claim from that customer's own ERP via MCP — not a politely-vague reassurance, not a copy from a stale data lake.
Traces to: Source-cited responses
Pre-built MCP connectors for the CM stack.
Including MES — the system most "AI ops platforms" cannot read because they were never built for the shop floor. OpsATC.AI is.
Reference adapter implementations are scaffolded for these platforms and validated against synthesized fixtures from public API documentation. Partner-sandbox re-records are pending; production validation happens during the first design-partner pilot. See platform integrations for the full reference-vs-scaffolded breakdown.
Manufacturing ExecutionShop-floor systems, yield, traceability
PLM & EngineeringRevision control, ECN, BOM
QMSQuality, CAPA, audit evidence
ERP & PlanningWork orders, demand, supply
Field Service & RMAService operations
Build visibility on day one, not after a six-month rollout.
No MES replication. No PLM extraction. No customer-portal data dump. The Captain reads your shop-floor systems, supplier portals, and customer-promise lanes live via MCP — and adapts on operator feedback, not retraining cycles. See the Day 1 to Day 90 timeline →
What we need
- ✓Read-only credentials per system you want orchestrated
- ✓Service accounts on those systems
- ✓Allow-list approval for OpsATC.AI's egress addresses
- ✓One-time field-mapping confirmation per connector
- ✓Pre-built connectors for MES, PLM, and the customer-portal stack you already operate
What we don't need
- ✗Historical data extraction from your data lake
- ✗Data warehouse seeding
- ✗Replicated copies of your operational data
- ✗Custom adapter work for standard platforms
- ✗Data-team involvement to begin
Your manufacturing data is dirty when we start — BOM drift between PLM and shop floor, build orders without supplier acks, missing serializations, test results that don't match work-order revisions, supplier master entries with two part-number conventions. The Captain Data Quality Detection Layer runs continuously: baseline at MCP connect, inline on every read, scheduled per record type, on-demand when an operator asks. Six issue classes, four detection modes, all surfacing through the Trusted Advisor card. No six-month cleanup project. See the full Data Governance architecture →
Bring your worst week. We'll walk through how it changes.
Thirty minutes, your live operational pain — a yield drop, an RMA cluster, a customer audit prep, a new-customer ramp. We'll walk through how the orchestration layer changes the response, the cycle time, and the cost. Written diagnosis within one business day.