Manufacturing operations handle ITAR-controlled data, customer financial information, proprietary product designs, and supply chain intelligence. Moving to the cloud doesn’t change your compliance obligations — it changes how you meet them. We design cloud security that satisfies auditors and protects your operation. Ford's Rouge Electric Vehicle Center, GM's Factory ZERO, and Stellantis's retooling of Jefferson North are rewriting what it means to build cars in Detroit. Tier 1 and Tier 2 suppliers along the I-94 corridor face a brutal reality: retool for EV drivetrains and battery modules, or lose contracts to greenfield competitors. The shift from internal combustion to electric has compressed product development cycles from years to months, and legacy Plex and QAD installations weren't designed for that pace.
Detroit suppliers who digitized scheduling and traceability before the EV transition hit are winning new battery-pack contracts; those still running paper-based PPAP are getting passed over.
Role-based access control, least-privilege policies, MFA enforcement, and service account governance. Every user and system has exactly the access they need and nothing more.
VPC segmentation, security groups, WAF, DDoS protection, and private connectivity to on-premise. Network architecture designed to isolate workloads and limit blast radius.
Data encrypted at rest (AES-256) and in transit (TLS 1.2+). Key management with customer-managed keys where compliance requires it. Encryption applied consistently across all storage and communication layers.
Architecture designed to meet SOC 2, ITAR, CMMC, NIST 800-171, and industry-specific requirements. Control mapping documentation that auditors can use directly.
Automated backups with defined RPO/RTO targets, cross-region replication for critical workloads, and documented DR procedures that are tested regularly — not just written.
Cloud-native security monitoring (GuardDuty, Security Center), centralized logging, alert routing, and documented incident response procedures. Threats detected and responded to, not just logged.
Identify all compliance requirements — regulatory, contractual, and internal policy. Map requirements to cloud security controls and identify gaps.
Design the security architecture — IAM, networking, encryption, monitoring, and DR — with controls mapped to each compliance requirement.
Implement security controls as infrastructure-as-code for consistency and auditability. Every control is version-controlled and reproducible.
Validate controls against compliance requirements. Generate control documentation, evidence packages, and audit-ready reports.
Cloud Security & Compliance for Detroit automotive operations - configured around local workflows, data ownership, and implementation governance.
Cloud Security & Compliance for Detroit aerospace & defense operations - configured around local workflows, data ownership, and implementation governance.
Cloud Security & Compliance for Detroit robotics & automation operations - configured around local workflows, data ownership, and implementation governance.
Cloud Security & Compliance for Detroit steel & metals operations - configured around local workflows, data ownership, and implementation governance.
Cloud Security & Compliance for Detroit financial services operations - configured around local workflows, data ownership, and implementation governance.
Cloud Security & Compliance for Detroit healthcare & medical operations - configured around local workflows, data ownership, and implementation governance.
Yes. AWS GovCloud and Azure Government provide ITAR-compliant infrastructure. We design the architecture to ensure ITAR-controlled data stays within compliant regions and access is restricted to US persons as required.
We design cloud architecture aligned to CMMC Level 2 (or Level 3) practices — CUI protection, access control, audit logging, and incident response. The architecture provides the technical controls; your organization provides the policies and procedures.
Yes. We offer managed security operations that include continuous monitoring, alert triage, vulnerability management, and incident response. Or we design the monitoring architecture and hand it off to your team.
We recommend quarterly DR testing for critical workloads. We design DR procedures with automated testing capabilities and conduct the initial DR test as part of implementation. Ongoing testing can be managed by your team or included in managed operations.
Most manufacturers are still running workflows that require a person to touch every exception, every order, every routing decision. AI agents eliminate that bottleneck — not by replacing your people, but by handling the work that was always below their pay grade.
Most manufacturers forecast demand with spreadsheets, gut feel, and last year's numbers adjusted by 5%. ML models trained on your actual order history, seasonality patterns, and market signals replace guesswork with predictions your planning team can act on.
Odoo Maintenance captures work orders, failure reasons, repair times, and equipment history. We build AI models on top of that data to identify failure patterns and recommend maintenance windows before breakdowns occur — no new hardware, no IoT infrastructure required.
Odoo Quality captures inspection results, non-conformances, scrap reasons, and lot traceability across every production order. We build AI models on top of that data to surface defect patterns, predict quality risk, and trigger alerts before scrap accumulates — no cameras, no hardware.
Most manufacturers price by cost-plus formula or by whatever the sales rep negotiated last time. AI pricing models factor in material costs, competitive positioning, customer segment, order size, inventory position, and market conditions — governed by business rules so every price stays within approved boundaries.
When an order hits your system, someone decides which warehouse ships it — usually based on habit, proximity, or whoever answered the phone. AI order routing makes that decision in real time, optimizing across inventory availability, shipping cost, delivery speed, and warehouse workload.
Manufacturers still process thousands of POs, invoices, RFQs, spec sheets, and BOLs manually — reading PDFs, retyping data into the ERP, and fixing the errors that come with it. Document intelligence extracts structured data from unstructured documents automatically, with validation rules that catch errors before they enter your systems.
Your dealers call or email to check stock before placing orders because they can't see what's available. We give them live ATP visibility across all your warehouses — available, allocated, in-transit, and expected replenishment dates — straight from your ERP and WMS.
We govern cloud migration in phases — every dependency mapped, every workload sequenced, every cutover window defined. Zero-downtime migration for manufacturers who can't afford an outage.
Most manufacturing AI projects die in the pilot phase. We deploy AI that integrates into your actual workflows -- demand forecasting, predictive maintenance, pricing optimization, and intelligent routing -- governed by operational data contracts.
Your demand planning process runs on last year\u2019s sales adjusted by a gut-feel percentage. ML models trained on your actual order history, seasonal patterns, and market signals produce forecasts that are measurably more accurate \u2014 and they improve automatically as more data accumulates.
Your legacy system holds critical data that modern applications need -- but it has no APIs, no webhooks, and no modern integration points. We build a REST/GraphQL API layer on top of your legacy system so new applications can access data without touching the core.
Metrotechs starts with the operating questions: which records are trusted, which workflows are manual, which systems own each decision, and where AI can safely improve throughput.
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