System Integration Automation

Real-time and scheduled data synchronisation between business systems — keeping customer records, product data, orders, stock levels and financial transactions consistent across CRM, ERP, e-commerce and other platforms without manual data entry or export-import.

• System mapping: define which fields sync between which systems
• Real-time sync via webhook on record creation or update
• Scheduled sync for systems without webhook capability
• Field transformation: map and convert data formats between systems
• Selective sync: sync only records matching defined criteria
• Sync status monitoring: success, error and pending queue
• Error alert: notify admin when sync fails
• Sync log: full history of every record transferred

Event-triggered automation chains that react to changes in one system and perform actions in others — a new deal won in the CRM triggers invoice creation in accounting, project creation in the PM tool and a welcome email in the marketing platform.

• Trigger event definition: record created, updated, status changed
• Action definition: create record, update field, send notification
• Multi-step automation chain from single trigger
• Delay step: wait for configurable period before next action
• Conditional action: perform action only if condition is met
• Test run with sample data before activating
• Automation run history with step-by-step log
• Pause and resume automation without deletion

Pre-built and custom integration automations between the SaaS tools the business already uses — Salesforce to Slack, HubSpot to Xero, Shopify to Mailchimp, Jira to Confluence — using n8n, Make.com or custom middleware to connect systems that don't talk to each other out of the box.

• Pre-built connector library for common SaaS combinations
• Custom connector development for systems without pre-built support
• n8n workflow development for self-hosted automation
• Make.com (Integromat) scenario development for cloud automation
• OAuth2 and API key authentication handling per connector
• Rate limit management to prevent API quota exhaustion
• Connector health monitoring and failure alerting
• Documentation of all active integrations and their data flows

Event-driven architecture for real-time data movement — systems publish events when something happens, subscribing systems receive and react immediately. Gives the business near-real-time data consistency without polling APIs every few minutes.

• Webhook receiver for inbound events from external systems
• Event queue management for reliable delivery
• Event replay capability for failed processing
• Dead letter queue for events that cannot be processed
• Event schema validation before processing
• Event-to-action mapping: which events trigger which actions
• Event monitoring dashboard: volume, latency, error rate
• Alert on event processing failure or queue backup

Bi-directional synchronisation between two systems of record — where both systems can create and update the same data — with conflict detection and resolution rules that prevent data loss when both sides update the same record before the sync runs.

• Bi-directional mapping: changes in either system sync to the other
• Conflict detection: identify when both systems updated the same field
• Conflict resolution strategy: last-write-wins or master-system-wins
• Manual conflict resolution queue for complex cases
• Duplicate detection on initial data migration
• Sync direction locking: certain fields only update from one direction
• Bi-directional sync testing against real data before go-live
• Conflict report: frequency and resolution of conflicts over time

Scheduled batch data transfer processes for systems that don't support real-time webhooks — nightly exports, daily stock updates, weekly CRM refreshes — with data extraction, transformation, validation and load into the target system on a reliable schedule.

• Schedule configuration: hourly, daily, weekly batch
• Data extraction from source via API, SFTP or database query
• Data transformation: clean, map and format for target system
• Validation rules: reject records that fail data quality checks
• Load to target: API call, database insert or file drop
• Run log with record counts: extracted, processed, failed
• Failed record handling: retry queue and error report
• Completion notification: success or failure per run