








































































































.webp)





















Yokogawa Exaquantum is a plant information management system serving as a manufacturing intelligence and historian platform for process industries.
Have any questions? We’re here to help You
Makini maintains a comprehensive data model built from analyzing thousands of industrial systems. When data flows through Makini, we automatically transform it from the source system's format into our standardized structure. For example, purchase orders from SAP, NetSuite, and Dynamics all return with consistent field names, data types, and structures. This normalization happens in real-time as data passes through the API. You also have access to raw data if needed for specific use cases. The unified model covers common entities like purchase orders, work orders, inventory items, vendors, and assets, with extensive field coverage across systems.
Makini Flows is our embedded workflow automation platform, built on n8n, which we consider the best workflow automation tool available. It's fully integrated into Makini and runs on our infrastructure. Flows allows you to build complex integration logic using a visual workflow builder—no code required, though code is supported for advanced use cases. Workflows can be triggered by schedules, webhooks, API calls, or events from connected systems. You can perform data transformations, implement conditional logic, call external APIs, and orchestrate multi-step processes. Flows includes over 1,000 pre-built connectors beyond Makini's industrial systems, enabling integrations with databases, messaging platforms, cloud services, and more. Most customer activations are completed using Flows due to its flexibility and ease of use.
Design your webhook receiver to handle duplicates and out-of-order webhooks, as network issues or retries can cause both scenarios. Keep the receiver lightweight—ideally writing incoming webhooks to a queue or reliable storage—then process them asynchronously. This prevents timeouts and allows your system to handle high-volume webhook spikes. Respond with a 200 status code immediately after receiving the webhook, before processing begins. Implement idempotency by tracking processed webhook IDs and skipping duplicates. Use constant-time comparison for signature verification to prevent timing attacks. If webhook processing fails, log the error but still return 200 to prevent unnecessary retries. Set up monitoring and alerts for webhook failures so you can investigate issues promptly. For critical workflows, combine webhooks with periodic polling as a fallback mechanism.
If you continue to experience problems with your NetSuite M2M connection after following the troubleshooting steps, contact Makini support at support@makini.io. You can also refer to the NetSuite API Documentation and Makini Documentation for additional technical details.
