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Tractian is an industrial IoT platform for predictive maintenance, using sensors to monitor equipment vibration, temperature, and performance in real-time.
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Makini supports over 2,000 industrial systems across ERP, CMMS, and WMS categories. This includes major platforms like SAP (ECC, S4/HANA, Business One), Oracle NetSuite, Microsoft Dynamics, IBM Maximo, and specialized industrial systems. We support both cloud-based and on-premises installations. If you need to connect to a system we don't currently support, we're committed to building that integration for you at no additional charge—most new integrations are completed within one business day. You can view our full list of supported systems at makini.io/integrations.
The initial sync occurs when you first connect a system and retrieves historical data to establish a baseline. This includes records from a configurable time period (typically 30-90 days) and can take several minutes to hours depending on data volume. Initial syncs are complete snapshots of the requested data. Incremental syncs occur on subsequent runs and retrieve only records created or modified since the last successful sync. Makini tracks sync timestamps and uses them to query for changes efficiently. Incremental syncs are much faster, usually completing in seconds to minutes. This approach minimizes API load on source systems while keeping your data current.
Makini provides several debugging tools. The dashboard shows detailed request logs including request/response payloads, headers, status codes, and timing. Each API request generates a unique request ID included in responses—provide this when contacting support for faster investigation. For workflow-based integrations, Makini Flows includes execution logs showing each step's input/output, timing, and any errors. Connection health monitoring shows sync history, error rates, and connection status over time. API responses include detailed error information with error codes and messages. For development, we recommend using API clients like Postman or Insomnia to interactively test API calls and inspect responses. Our API documentation includes request/response examples for all endpoints.
Makini provides several performance monitoring capabilities. API responses include timing information showing request processing time. The dashboard includes performance metrics showing average response times, throughput, and error rates over time. You can set up alerts for performance degradation or error rate increases. Each request generates a unique request ID that enables detailed performance analysis. For workflow-based integrations, execution logs show per-step timing, helping identify bottlenecks. We recommend implementing client-side monitoring to track end-to-end latency including network time. Monitor trends over time rather than individual requests—occasional slow requests are normal, but sustained increases may indicate issues requiring investigation.
