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Integration timelines vary by complexity. For standard implementations with no customizations, connections can be live within 1-2 weeks. This includes authentication setup and basic workflow configuration. For implementations requiring custom workflows or specific business logic, timelines typically range from 2-6 weeks depending on the scope. Complex enterprise deployments with multiple systems and custom requirements may take 6-10 weeks. These timelines are significantly shorter than traditional integration projects, which often take 2-24 months.
Makini provides a `/sync-status` API endpoint that returns the current synchronization state for a connection. The response includes the last successful sync timestamp, sync status (in progress, completed, failed), any error messages, and the next scheduled sync time. You can query this endpoint to monitor sync health and detect issues. For workflow-based syncs using Makini Flows, each workflow execution is logged with detailed status information including start time, completion time, success/failure status, and any errors encountered. The Makini dashboard also provides visual sync status monitoring across all connections.
Makini supports create, read, update, and delete (CRUD) operations, though availability varies by system and entity type. Most systems support creating and updating core entities like purchase orders, work orders, and inventory items. Read operations are universally supported across all entity types. Delete operations are less commonly supported due to system constraints—many industrial systems use soft deletes or status changes rather than true deletion. Update operations may be limited to specific fields depending on system configuration and business rules. For example, some systems prevent modifying purchase orders after approval. We recommend validating specific operation support for your use case during the technical deep dive.
Makini uses cursor-based pagination for retrieving large datasets. API responses include a `next_cursor` field when additional results are available. To retrieve the next page, include the cursor value in your next request: `GET /api/v1/purchase-orders?cursor=CURSOR_VALUE`. Cursor-based pagination is more reliable than offset-based pagination because it handles data changes between requests—if records are added or deleted while you're paginating, you won't miss records or see duplicates. Page size is configurable up to a maximum limit (typically 100-500 records per page depending on entity type). For optimal performance, use the largest page size your application can handle efficiently. The API response also includes total count when available from the source system.
