Understanding the systems.
Engineering the connections.

Enterprise & Manufacturing Systems

Integration work starts with the responsibilities of each system and the data it owns. SAP and ERP platforms, MES, LIMS and legacy systems often represent different parts of the same business or manufacturing process.

• Analyse system boundaries, interface dependencies and data ownership.
• Work with SAP PI/PO within the wider integration landscape.
• Connect enterprise requirements with manufacturing and laboratory data flows.

Typical outputSystem context and interface decisions that reflect the wider landscape.

Integration Architecture

Choose integration patterns around the process, the data and the behaviour required between systems. Document how the parts work together and where failure needs to be handled.

• Design synchronous API interactions and event-driven integrations.
• Define data mapping, error handling and retry strategies.
• Prepare interface specifications and sequence flows for delivery teams.

Typical outputA clear design for interactions, responsibilities and failure behaviour.

APIs & Messaging

REST and SOAP APIs support request / response interactions. Kafka and event-driven architecture support message flows between producers and consumers. Each approach needs explicit contracts and operational expectations.

• Specify API integration requirements and OpenAPI descriptions.
• Define event structures and producer / consumer responsibilities.
• Consider duplicate messages, ordering and recovery in the integration design.

Typical outputAPI and messaging contracts aligned with the project’s system behaviour.

Contracts & Data

A useful contract describes both the data structure and its meaning. JSON, XML and XSD provide formats and schemas; specifications explain validation, mapping and compatibility between systems.

• Define required fields, structures, types and validation rules.
• Map source and target data, including transformation behaviour.
• Document schema changes and their impact on consuming interfaces.

Typical outputData contracts that support consistent implementation and testing.

Data Analysis

SQL and PostgreSQL support investigation when data in one system does not match another. Analysis connects database findings to interface behaviour and the integration’s expected outcome.

• Investigate data discrepancies and message-related records.
• Validate mappings and transformation results.
• Support troubleshooting with queries and data validation.

Typical outputEvidence to explain data issues and verify corrections.

Industrial Integration

Manufacturing integrations connect business processes with production and laboratory operations. ISA-95 provides supporting context for understanding enterprise and manufacturing responsibilities.

• Analyse MES, ERP and LIMS interactions in the enterprise / OT / IT context.
• Clarify process dependencies and system / data flows.
• Design and test integration boundaries within agreed system constraints.

Typical outputIntegration designs grounded in manufacturing and enterprise context.