API integration services

The first stage is a short technical check of both systems, before the price is fixed. We read the API documentation and make real test calls. We look for the things that decide the design: whether the system sends webhooks or has to be polled, how it authenticates, what its rate limits are, and whether records can change or disappear after they are sent.

Then we write a one-page mapping for you to approve: which system owns each field, what happens on create, update and cancel, and which errors need a person. From you we need access to both systems, someone who knows how the data is used today, and a few real examples, including the awkward ones: a cancelled order, a merged contact, a partial refund.

Each week you see the integration running in a test environment with your example records, with a note on what was built and which decisions are open. Before launch, where the systems allow it, the integration runs on live data in a dry-run mode that writes to a log instead of the target system, so you can compare its results before anything changes.

The mapping covers:

• Each field, its source, its format and who may change it
• How records in the two systems are matched
• What happens when a record is edited, cancelled or deleted at the source
• Which failures retry on their own and which go to a person

The worst integration failures are quiet. A token expires, a partner renames a field, a webhook is rejected, and records simply stop arriving. Someone notices days later, often a customer. We design for that moment from the start.

Each incoming event is stored before it is processed, so nothing depends on a single attempt. Processing is idempotent: the same event applied twice still leaves one record, matched on the source system's ID and version. Changes made after a record was created arrive as new versions, not as duplicates. Failed attempts are retried with increasing delays and then moved to a dead-letter queue, where a person sees the payload and the error and can replay it after a fix.

Monitoring checks outcomes, not only errors. An alert fires when the oldest unprocessed message is too old, when the dead-letter queue is not empty, or when a scheduled reconciliation finds records in one system that are missing from the other. Each record carries a trace ID through both systems, so “what happened to this order?” has an answer in the logs.

The guest benefits platform works this way. Bookings arrive as signed webhooks, and each one is stored together with an outbox record in one transaction. Date changes, guest count changes and cancellations flow through as versioned updates. A queue-driven worker delivers updates to the member app, with retries, dead-letter queues and a scheduled safety net that re-sends anything that did not arrive. In the load board automation, offers that are still open are re-sent to the platform's ingest API, so it knows they are current.

The integration runs on your cloud account, with credentials in your own secrets manager. You get the code with tests that replay recorded API responses, failures included, the infrastructure as code and the approved mapping, kept up to date. The runbook explains how to read the dashboard, replay a failed message, run a reconciliation by hand and renew each credential before it expires.

APIs change, so an integration needs a little care after launch. When a provider announces a new API version or retires a field, the mapping shows which parts are affected. Monthly support covers those changes and the monitoring, or your team takes them over with the runbook.

An integration is not always the whole answer:

• Connecting systems is one step in a longer process with approvals and people? Business process automation covers the whole process.
• The data has no proper home and lives in spreadsheets between the systems? Custom CRM & internal tools gives it one.
• You need a platform with its own users and its own API? See Custom software development.