A build-to-order Business Central AL extension that ingests machine sensor data, applies AI anomaly and failure-risk detection, and auto-creates predictive maintenance work orders before equipment fails. Installed as a per-tenant extension and supported by ECOSIRE. One-time license from $799.00 USD for Dynamics 365 BC (build-to-order) — includes 12 months of updates and support.

A build-to-order Business Central AL extension that ingests machine sensor data, applies AI anomaly and failure-risk detection, and auto-creates predictive maintenance work orders before equipment fails. Installed as a per-tenant extension and supported by ECOSIRE.
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Predictive Maintenance (AI) is a custom-built extension for Microsoft Dynamics 365 Business Central that turns raw machine sensor telemetry into proactive maintenance work orders — before a breakdown happens. ECOSIRE builds it, installs it as a per-tenant extension on your Business Central environment, and supports it. This is not an instant AppSource download; it is a scoped engagement delivered to fit your assets, sensor sources, and reliability workflow.
Sensor telemetry ingestion via the Business Central REST/OData v4 API or a customer push gateway into a dedicated AL readings table
Scheduled trend analysis and moving-window baselining driven by a Business Central Job Queue entry
AI/ML anomaly detection and failure-risk scoring via an external Azure Machine Learning or Azure OpenAI endpoint (model retrainable without AL changes)
Remaining-useful-life (RUL) estimation surfaced on asset and maintenance pages
Auto-created predictive maintenance work orders fired by AL event subscribers when a risk threshold is crossed
Downtime-vs-maintenance cost optimization that derives work-order priority from configurable cost parameters
The extension is written in AL and ships new tables plus table and page extensions on your maintenance and item/asset master data. Sensor readings arrive via the Business Central REST/OData v4 API (or a customer gateway pushing JSON) into a dedicated readings table. A Job Queue entry runs trend analysis and anomaly scoring on a schedule you define. Failure-risk and remaining-useful-life scoring is performed by an AI/ML model called over HTTPS — typically an Azure Machine Learning endpoint or Azure OpenAI / Dataverse + Power Platform AI service — so your model can be retrained without changing AL code.
When a machine crosses a risk threshold, an event subscriber auto-creates a predictive maintenance work order, populates the affected asset, suggested tasks, and a priority derived from a downtime-vs-maintenance cost comparison. Reliability engineers see trend charts, anomaly flags, and RUL estimates directly on Business Central pages, with drill-down to the underlying readings.
Everything ships with a dedicated permission set, telemetry-friendly logging, and clean uninstall. Because it is per-tenant, your customizations never collide with Microsoft's monthly updates, and ECOSIRE re-tests against each major BC release. You own the data; we own keeping it working.
Owns asset uptime at an asset-intensive plant and wants failure-risk signals and RUL estimates surfaced inside Business Central so predictive work orders are raised automatically instead of relying on calendar-based PM schedules.
Needs to cut unplanned downtime and balance maintenance spend against failure cost. Uses the cost-optimization scoring to prioritize which auto-created work orders get crews first.
Responsible for the BC environment and integrations. Cares that the solution is a clean per-tenant extension with a scoped permission set, observable Job Queue jobs, and no base-app modification that breaks Microsoft updates.
Compre la licencia en ecosire.com y descargue el módulo ZIP Predictive Maintenance (AI) desde el panel de su cuenta.
Extraiga el ZIP en su carpeta de complementos personalizados de Odoo en el servidor (o cárguelo a través de Aplicaciones > Instalar desde archivo en Odoo.sh/runbot).
Active el modo de desarrollador, abra Aplicaciones, haga clic en Actualizar lista de aplicaciones, busque Predictive Maintenance (AI) y presione Instalar.
Abra el nuevo menú, pegue su clave de licencia de ECOSIRE, conecte cualquier credencial externa (Shopify, Amazon, Stripe, etc.) y guarde.
Ejecute la prueba de conexión integrada, sincronice sus primeros 10 registros y programe el cron recurrente. Póngase en contacto con el soporte si algo falla.
| Criterio | ECOSIRE | Construcción personalizada | Competidor | Odoo Nativo |
|---|---|---|---|---|
| AI anomaly detection and failure-risk scoring built in | ||||
| Auto-created predictive maintenance work orders from sensor thresholds | ||||
| Remaining-useful-life (RUL) estimation surfaced in Business Central | ||||
| Tailored to your specific assets, sensors, and maintenance workflow | ||||
| Delivered as a clean per-tenant extension (no base-app modification) | ||||
| Built, installed, and supported for you with a defined SLA | ||||
| Sensor ingestion via BC REST/OData API or customer gateway | ||||
| Model retrainable / swappable without AL code changes |
No. This is a build-to-order engagement. ECOSIRE builds the AL extension to fit your assets and sensor sources, then installs it as a per-tenant extension on your Business Central environment. There is no public AppSource listing or self-service download — you get a solution tailored to your reliability workflow and deployed for you.
A typical build runs about 3 to 5 weeks after scoping sign-off, depending on the number of asset types, sensor data complexity, and which AI/ML endpoint you use. We start with a scoping document, build and test in a sandbox, then schedule the production install with you. The price covers the standard scope; unusual sensor protocols or many distinct asset models may extend the timeline, which we agree before starting.
Every build includes a warranty/support window with agreed response times. Because it is a per-tenant extension, ECOSIRE re-tests it against each major Business Central release and ships compatibility updates. Beyond the included window, we offer a support retainer covering bug fixes, threshold and model tuning, and adapting to new sensor sources or asset lines as your plant grows.
Readings can arrive through the Business Central REST/OData v4 API or via a gateway that pushes JSON from your historian, IoT hub, or SCADA layer. The anomaly and RUL scoring runs on an external endpoint — commonly Azure Machine Learning, Azure OpenAI, or a Dataverse/Power Platform AI service — so you can retrain or swap the model without us rewriting AL code. We confirm the exact integration during scoping.
No. The solution is delivered as a per-tenant extension using table extensions, page extensions, and event subscribers — it never modifies the base application. This is the supported customization model, so Microsoft's monthly and major updates apply normally. ECOSIRE validates the extension against each major release and provides any needed fixes.
A build-to-order Business Central AL extension that ingests machine sensor data, applies AI anomaly and failure-risk detection, and auto-creates predictive maintenance work orders before equipment fails. Installed as a per-tenant extension and supported by ECOSIRE.