Automating Error Management for a
UK-Based D2C Electronics Brand
Client Overview
Business Objective
The client needed to stabilize their mission-critical operations and achieve cost predictability as they scaled. Their existing integration costs were skyrocketing unpredictably during promotional periods due to data-usage pricing models. Furthermore, their IT team was overwhelmed by manual troubleshooting of failed orders. Their primary aim was to migrate to a modern iPaaS that offered predictable operational costs through endpoint-based licensing and utilize advanced automation to reduce manual intervention in error handling.
Industry
E-commerce
Platform
Celigo
Service
Automated Error Management
Challenges
Rising Costs
The previous integration platform was charging based on the amount of data being processed.
High Volume of Errors
Errors like inventory mismatches, incorrect addresses and API failures had to be manually identified.
Custom Scripts Dependency
Every time a new 3PL partner was added, new custom integrations had to be built from scratch.
Lack of Visibility
No clear visibility into integration failures led to problem discovered only after customers reported problems.
Slow Resolution Time
Since technical and business errors were mixed together in logs, identifying the root cause took time.
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Strategic Assessment and Cost Optimization
NeosAlpha analyzed the complete data flow between Shopify, NetSuite, Zendesk, and 3PL systems. Based on this, they recommended moving to Celigo integrator.io, which uses endpoint-based pricing. This ensured that costs were fixed based on connected systems rather than the volume of data being processed, bringing predictability to integration expenses.
Standardized Integration Architecture
The integration architecture was redesigned using standardized connectors and reusable templates. Orders from Shopify Plus were synced into Oracle NetSuite as sales orders, while fulfillment data was transmitted to 3PL partners as shipment requests. In turn, shipment updates from logistics providers were fed back into NetSuite as item fulfillment records, and customer issues from Zendesk were synchronized as customer and case records.
AI-Driven Error Management
Instead of basic error logs, Celigo’s AI was configured to automatically classify errors. It could differentiate between technical issues like API failures and business issues like missing or incorrect data. This made it easier to understand and act on errors quickly.
Automated Recovery and Routing
Once errors were classified, automated workflows were introduced. Technical errors were handled through automatic retries, resolving many issues without human intervention. Business-related errors were routed directly to the relevant teams; for example, warehouse teams for shipping issues and customer support for address-related problems using tools like Slack and Jira.
Post-Migration Enablement
NeosAlpha trained business users to monitor integrations through dashboards, reducing dependency on technical teams. A governance model was also implemented to manage new integrations efficiently while maintaining cost control.
Results
Achieved Cost Predictability
Integration costs became stable with endpoint-based pricing, even during high transaction volumes and peak sales periods.
Reduced Manual Effort in Error Handling
AI-based error classification and auto-retries eliminated most manual intervention for routine integration issues.
Faster Issue Resolution
Errors were routed directly to the right teams, reducing resolution time from days to just a few hours.
Accelerated Partner Onboarding
Standardized integration templates enabled faster onboarding of new 3PL partners with minimal development effort.
Technology Stack
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