Software That Connects the Factory Floor to the ERP

We work through each ERP's supported integration path: the Service Layer and DI API for SAP Business One, the contract-based REST API and OData interface for MYOB Acumatica, SuiteTalk and RESTlets for NetSuite, and the published APIs for Microsoft Dynamics 365 Business Central and Finance and Operations. Older on-premises ERPs without a usable API can often be integrated through their database views, scheduled exports or an existing middleware layer. We confirm the exact route, licence requirements and any partner involvement during discovery, before quoting a fixed price.

Usually build around it. An ERP is expensive and disruptive to replace, and most of the pain manufacturers describe comes from the gaps between the ERP and everything else, not the ERP itself. We keep the ERP as the system of record for orders, stock and costing and build the missing pieces beside it: shop-floor capture, quality workflows, traceability and reporting. If your ERP genuinely can't support where the business is going, we'll say so and help you scope a replacement with an ERP partner rather than rebuild it ourselves.

Yes, this is one of the most practical uses of AI in manufacturing. A document processing pipeline reads incoming PDFs and scans, extracts fields such as supplier, PO number, batch or heat number, quantities and test results, checks them against the purchase order and specification in your ERP, and files the document against the right receipt. Each extracted field carries a confidence score, so staff review only the uncertain values and anything that fails a specification check, rather than retyping every document.

We build the data foundation that predictive maintenance depends on: collecting machine and sensor data, linking it to assets, jobs and maintenance history, and making it queryable. On top of that we can build condition alerts and anomaly detection. Whether prediction is worth it depends on having enough history, including failures, for the machines that matter. We assess that honestly in discovery, and often recommend starting with condition monitoring and better maintenance records before any prediction model.

Often, if it is scoped tightly. We start with a paid discovery to find the one or two workflows where connecting systems or removing re-keying saves the most time, then build those at a fixed price. All code goes into your own repository, the system runs in Australian cloud regions or on your own infrastructure, and we document it so your team or another provider can support it. Some manufacturing R&D may be eligible for the R&D Tax Incentive; speak to a registered R&D tax agent, as we are not one.

Yes, if it is designed for it from the start. Shop-floor apps should work offline and sync when the connection returns, support shared tablets with quick badge or PIN sign-in, use large touch targets that work with gloves, and scan barcodes or QR codes rather than relying on typing. We test on the actual devices and in the actual environment before rollout.

It depends on how many systems are involved and how much the shop floor needs to change, so we fix the price after a paid discovery. As a guide, the typical Australian market ranges on our service pages are $15k to $40k for a focused integration or background job service, $30k to $60k for AI processing of one document type such as supplier certificates, and $50k to $120k for a production and quality data platform with one live use case (AUD, ex GST). Most manufacturers start with one workflow rather than all of them.

A manufacturing execution system (MES) manages and records work on the shop floor: scheduling, work orders, data capture, quality and traceability. Large or highly regulated plants often justify a full MES. Many mid-sized manufacturers get most of the value from a few targeted apps connected to the ERP, covering scheduling, shop-floor capture and batch traceability, at lower cost and disruption. We compare both routes honestly in discovery.

For equipment that exposes data, yes. Many modern machines and PLCs publish data over industrial protocols such as OPC UA or MQTT, often through an edge gateway, and older machines can be retrofitted with sensors. We build the software side: collecting that data, timestamping it, linking it to jobs and assets, and making it available to dashboards and maintenance workflows. Any controls or electrical work on the machines themselves stays with your automation integrator or electrician.