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Integration development between Exact Online and Lyra WMS for client from Netherlands
- Authors
- Name
- ByteGeometry
- @ByteGeometry
Stock Software integration Case Study - Exact Online + Lyra WMS
Context
A logistics-focused company in Netherlands managing operations through Exact Online (for accounting and order management) and Lyra WMS (for warehouse operations) faced a critical bottleneck: disconnected systems leading to manual order handling, fulfillment delays, and limited visibility across sales and inventory workflows. The client needed a robust integration between Exact Online and Lyra WMS to automate four key areas - sales order flow, purchase orders, inventory updates, and delivery confirmations. Business-specific logic added complexity, such as the need to filter out drop shipment items from warehouse operations. The integration had to be production-ready before the company’s peak season, with strict requirements for reliability, scalability, and auditability - making precision and efficiency critical from day one.
Solution
We designed and implemented a custom Python based middleware integration to serve as a reliable bridge between Exact Online and Lyra WMS. The solution revolves around a scheduled polling system that retrieves new sales and purchase orders from Exact Online every 10 to 30 minutes. Orders undergo business logic filtering to exclude drop shipment items from being forwarded to Lyra WMS, ensuring warehouse processes only handle stock items. Purchase orders were synchronized with correct warehouse associations, preserving operational accuracy. Shipment and receipt updates flowed back from Lyra WMS to Exact Online, keeping sales orders and purchase orders status aligned in real time. To handle Exact Online’s API rate limits, we implemented batch processing with intelligent throttling and retry mechanisms. Data storage was designed to retain all exchanged data for a full year to meet auditing requirements. Comprehensive error logging and alerting were included to maintain reliability, and the system was stress-tested under load conditions before deployment. Collaboration with Lyra WMS experts ensured seamless API usage and robust handling of edge cases.
Technology and Tools
The integration was built using a custom Python middleware approach, primarily leveraging FastAPI for its asynchronous capabilities and scalability. We utilized the official Exact Online API with OAuth2 authentication to securely access sales and purchase order data, while Lyra WMS’s API was accessed via API key authentication. To optimize API usage and respect rate limits, we implemented batch processing with backoff strategies. For data storage, we used PostgreSQL to persist drop shipment mappings, transaction logs, and full data retention for one year, enabling auditing and troubleshooting. The polling scheduler was built with cron jobs, balanced to minimize load and ensure timely synchronization. Error handling for centralized logging and integration with alerting tools to flag failures promptly. Continuous collaboration with the Lyra WMS technical team helped ensure the API interactions met expected standards, minimizing deployment risks.
Results
The integration successfully automated end-to-end order and inventory synchronization between Exact Online and Lyra WMS, eliminating manual data entry and reducing order processing times by over 70%. Drop shipment filtering ensured warehouse operations were optimized, preventing unnecessary handling of non-stock items. The system handled API rate limits gracefully, maintaining uninterrupted data flow even during peak hours. Real-time updates of shipment and receipt statuses improved operational visibility and accuracy across sales and procurement teams. The full one-year data retention provided peace of mind for auditing and compliance. Post-deployment support ensured smooth adoption, with minimal downtime and quick resolution of edge cases. Overall, the client gained a scalable, reliable solution that boosted operational efficiency, reduced errors, and supported business growth ahead of their peak season.