IT System Integration Guide

When does a business need IT system integration?

You need integration when staff regularly copy data between applications, reports require manually merging exports, and the same customer or order details differ from one system to another. Another clear signal is customer service delays caused by waiting for information held in a different department or tool. These costs grow with every new customer.

Typical scenarios include connecting an online store with the ERP and warehouse, syncing the CRM with invoicing, routing form submissions into the helpdesk and feeding a data warehouse for reporting. In each case the manual step is a bottleneck that grows as the business scales.

It is worth estimating how many hours per week the team spends moving data and fixing mismatches. Integration often pays back faster than expected and opens the door to further automation, covered in our business process automation guide.

Integration also has strategic value. When data across systems is consistent, you can build reliable management reporting, deploy AI assistants that see the full customer history and add new sales channels without handling each one by hand.

How do you audit your systems before integrating them?

List every system with its owner, available APIs and data formats. For each data type, such as customer, product or order, decide which system is the source of truth. Document existing integrations and the manual work that replaces missing ones. The result is a data flow map and a prioritised list of integrations to build first.

The audit starts with an inventory: system name, version, vendor, hosting, available interfaces (REST, SOAP, file exports, direct database access) and licence restrictions. This is often when forgotten scripts and spreadsheet macros that daily work depends on come to light.

The most important outcome is agreeing on sources of truth. If customer data can be edited in both the CRM and the ERP with no precedence rule, integration will overwrite changes and create conflicts. Agree on shared identifiers too: a common customer number or product SKU saves a lot of record-matching pain later.

Which integration pattern should you choose: point-to-point, middleware or event-driven?

Point-to-point connections between pairs of systems are fine when you have only a few applications. As systems multiply, a middleware or iPaaS layer that centralises integration logic works better. Event-driven architecture with a message broker such as RabbitMQ or Kafka offers loose coupling and scales well with high traffic and many consumers of the same data.

Point-to-point links are quick to build, but the number of connections grows rapidly with each new system, and a change in one application can force fixes in several integrations at once. It is a sensible starting point when you connect two or three tools.

Middleware, whether a custom integration service or an iPaaS platform, handles data mapping, queuing and error handling in one place. Event-driven architecture goes further: a system publishes an event, such as an order being created, and interested applications consume it. It demands a more mature team but makes adding new systems far easier.

Should data synchronisation happen in real time?

Not always. Real time matters where delay hurts customers or operations, for example stock levels, payments or bookings. Reporting, bulk accounting entries and catalogue syncs can often run in batches every few minutes or once a night, which is simpler to build, cheaper to run and puts less load on the source systems you depend on.

Real-time integrations rely on webhooks or events, where the source system announces a change itself. That requires queues and retries, because the receiving system may be temporarily unavailable. Batch integrations pull changes at set intervals and are easier to troubleshoot.

Most companies combine both. An order reaches the warehouse instantly, while a full price list sync runs overnight. Keep an eye on vendor API rate limits too, as polling too often can lead to throttling, a blocked account or extra charges.

When choosing, ask the team that uses the data how quickly they really need it and what happens if it arrives a few minutes late. The answer often simplifies the design and cuts infrastructure costs with no loss to the business.

How do you integrate a legacy system that has no API?

There are several options: reading and writing directly to its database, exchanging files such as CSV or XML through an agreed location, building a thin API layer around the system or, as a last resort, using an RPA bot. The choice depends on how stable the system is and whether you plan to replace it soon.

Direct database access is fast but risky: it bypasses the application's business logic and may break after an update. A safer route is a custom API layer that wraps the old system and exposes it to the rest of your stack in a modern way, so other applications never need to know its internals.

That layer also makes later replacement easier, because integrations depend on the API rather than the application itself. We describe this approach in our legacy ERP modernisation case study for a logistics company. Our legacy system migration guide covers planning such changes in more depth.

How do you keep integration APIs secure and reliable?

Use token-based authentication such as OAuth 2.0, least-privilege access and encrypted transport. Design APIs with versioning and OpenAPI documentation so changes do not break existing connections. An API gateway lets you manage access, rate limits and logging centrally. If personal data flows through integrations, check GDPR obligations and processing agreements with every vendor involved.

Each integration should have its own credentials with the narrowest scope possible. If a key leaks, you can revoke it without affecting other connections. Store secrets in a vault or secrets manager, never in code or spreadsheets.

When personal data is involved, decide which fields the target system genuinely needs and do not copy the rest. Check where vendors store data and whether processing agreements are in place. This matters especially when connecting a CRM with language models, as in CRM and AI integration.

How do you monitor integrations and handle errors?

Every integration should log operations centrally, retry automatically on temporary failures and send unprocessable messages to a dead letter queue for review. Set alerts on rising error rates and latency. That way your technical team spots problems first, rather than a customer, the warehouse or the finance department discovering missing data days later.

The worst case is an integration that fails silently. Orders stop reaching the warehouse and nobody notices for days. Monitoring should therefore be designed together with the integration, not bolted on later. Core metrics are messages processed, error rate and processing time.

Idempotency is another good practice: processing the same message twice must not create duplicate invoices or orders. Provide a simple dashboard where a business user can see failed operations and replay them after fixing the data, without involving a developer.

How much does IT system integration cost?

Cost depends on the number of systems, API quality, data volume and real-time requirements. Individual connections are usually estimated in hours at EUR 33. A full integration platform linking many systems is comparable to a mid-size custom system, around EUR 14,000 - 47,000. Ongoing maintenance starts from EUR 200, covering monitoring, hosting and adjustments to vendor API changes.

Costs rise most with undocumented systems or missing APIs, inconsistent data that needs cleaning and mapping, and strict availability requirements. A thorough audit and phased delivery bring them down: start with the most painful data flow, then add the next.

Budget for running costs as well: iPaaS licences if you use one, hosting, monitoring and changes when vendors update their APIs. We explain how to estimate such projects in more detail on our custom software cost page.

Before signing, ask the vendor to break the estimate down by phase and data flow. That makes offers comparable, lets you drop lower-priority items and gets the first integration live before the whole programme is finished.