Off-the-shelf tools force manufacturers to change how they work. Custom software should do the opposite -- fit your workflows, integrate with your systems, and solve the specific operational problems your business actually has. Charlotte's manufacturing identity is splitting in two directions at once. Legacy energy suppliers built around Duke Energy's grid infrastructure are retooling for EV components, while Siemens Energy and ABB push turbine and switchgear production along the I-85 corridor toward full digital thread adoption. The result is a workforce fluent in heavy electrical assembly but largely unfamiliar with connected factory operations.
Charlotte's Tier 1 automotive suppliers are being forced into digital compliance by OEM mandates from BMW Spartanburg and the incoming VinFast plant, but most are still running disconnected Epicor and SAP instances with no real-time shop floor visibility.
Purpose-built portals for dealer ordering, contract pricing, account management, and order tracking -- integrated directly with your ERP so pricing, inventory, and order status are always accurate.
Lightweight applications for production tracking, work order management, quality inspection logging, and operator dashboards. Built around your manufacturing process, not a generic MES you\u2019ll never fully adopt.
Custom inventory lookup tools, barcode scanning workflows, cycle count applications, and warehouse task management -- designed for how your warehouse actually operates, integrated with your WMS or ERP.
Automate the manual processes that burn hours every day: order entry from EDI or email, quote generation, approval routing, freight calculations, and exception handling.
Real-time dashboards pulling from ERP, WMS, CRM, and production systems into a single view. Built for the metrics your leadership team actually tracks, not the ones a BI vendor thinks you should.
Build the integration layer between your systems -- ERP to e-commerce, WMS to shipping, CRM to quoting. REST APIs, webhooks, middleware, and ETL pipelines governed by data contracts.
Map the workflows, pain points, and system landscape. Identify which problems justify custom software vs. configuring existing systems. Define data contracts and integration boundaries before writing a line of code.
Design the technical architecture, user workflows, and integration points. Lock scope to the smallest release that solves the target problem. Define ownership, hosting, and support model upfront.
Develop in 2-week sprints with stakeholder review at every milestone. Working software demonstrated against real operational scenarios -- not mockups, not slide decks, actual functioning tools.
Connect to your ERP, WMS, and other systems. End-to-end testing with real transaction data across the full workflow. Performance, security, and failure-mode validation before launch.
Governed rollout with user training, monitoring, and 30/60/90-day hypercare. Post-launch optimization based on actual usage patterns and operational feedback.
Custom Software Development for Manufacturers for Charlotte automotive operations - configured around local workflows, data ownership, and implementation governance.
Custom Software Development for Manufacturers for Charlotte energy infrastructure operations - configured around local workflows, data ownership, and implementation governance.
Custom Software Development for Manufacturers for Charlotte aerospace & defense operations - configured around local workflows, data ownership, and implementation governance.
Custom Software Development for Manufacturers for Charlotte food & beverage operations - configured around local workflows, data ownership, and implementation governance.
Custom Software Development for Manufacturers for Charlotte financial services operations - configured around local workflows, data ownership, and implementation governance.
Custom Software Development for Manufacturers for Charlotte healthcare & medical operations - configured around local workflows, data ownership, and implementation governance.
We select the stack based on your requirements and existing infrastructure. Common choices include React, Node.js, Python, .NET, and PostgreSQL. For manufacturers already on Odoo, we build custom modules directly on the Odoo framework. The technology serves the operation, not the other way around.
Typical projects deliver a first working release in 6\u201310 weeks. Dealer portals and operational tools can launch in 8\u201312 weeks. Complex multi-system integrations with production dashboards take 3\u20135 months. We scope to deliver usable software fast, then iterate.
Yes. We build direct integrations with Odoo and legacy systems including AS/400. Every integration is governed by data contracts -- source of truth, sync frequency, and failure handling defined before development starts. All integration infrastructure runs on AWS.
Yes. You own 100% of the source code, documentation, and deployment artifacts. No licensing fees, no vendor lock-in, no recurring charges for software you paid to build. We can provide ongoing support and development, but ownership is yours from day one.
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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