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Makini is a unified API platform for industrial systems integration. We provide connectivity to over 2,000 ERP, CMMS, and WMS systems through a single, standardized API. Instead of building separate integrations for each system, you connect once to Makini and gain access to all supported platforms. This approach transforms integration projects that typically cost tens of thousands of dollars and take months into a manageable operational expense with deployment times of 1-2 weeks.
Makini's purchase order data model includes comprehensive field coverage across all major ERP systems. Standard fields include order number, line items, vendor information, quantities, unit prices, dates (order date, required date, delivery date), status, currency, ship-to and bill-to addresses, payment terms, and custom fields. Each line item includes product/material codes, descriptions, quantities, unit of measure, pricing, and delivery information. The specific fields available depend on the source system's capabilities. You can view the complete field mapping for any connected system in the Makini dashboard, and custom fields can be added as needed for your specific requirements.
Webhooks allow Makini to notify your application of events in real-time. To set up webhooks, configure a webhook URL in your connection settings or during the initial connection flow. Your webhook endpoint must accept POST requests, respond within 10 seconds with a 200 status code, and use HTTPS with a valid SSL certificate. Makini will send webhook payloads to your endpoint when configured events occur, such as sync completion, connection status changes, or errors requiring attention. We recommend keeping your webhook receiver lightweight—ideally just writing the payload to a queue for asynchronous processing—to avoid timeouts and ensure reliable delivery.
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.
