Infor CloudSuite and Rippling integration

What moves between them

Employee records flow from Rippling into Infor CloudSuite. New hires, terminations, rehires, and department changes in Rippling are read by polling or webhook and mapped to CloudSuite GL dimensions, cost centers, or vendor records so payroll allocations land on valid accounts. Payroll runs are read from Rippling and transformed into labor cost journals that post into CloudSuite's general ledger on a schedule tied to your payroll calendar. Department and cost center mappings are maintained in both directions so payroll deductions and withholdings align to the correct GL accounts.

How ml-connector handles it

ml-connector stores Infor CloudSuite OAuth credentials and Rippling API key or OAuth token encrypted and uses the CloudSuite ION API Gateway base URL provided per customer to authenticate. It polls Rippling's employee list on a schedule to detect new hires, terminations, and updates, and transforms those events into GL dimensions or vendors in CloudSuite using the appropriate M3 or SyteLine API calls. Payroll run data is read from Rippling on a schedule matching your pay period and mapped to labor cost journals that are posted into CloudSuite's general ledger through the APS100MI (invoices) or direct GL posting endpoints, allocated to the correct cost center. Because Infor CloudSuite M3 Add and Update calls are not idempotent by default, ml-connector implements external deduplication by tracking CloudSuite record IDs to prevent duplicate postings on retry. Rippling rate limits are respected by backing off on 429 responses. Every record carries a full audit trail and can be replayed if a downstream call fails.

A real-world example

A mid-sized professional services firm uses Infor CloudSuite for finance and project accounting and Rippling for payroll and employee management across two offices. Before the integration, the finance team exported payroll registers from Rippling every pay period and manually created labor cost entries in CloudSuite's general ledger, allocating them to project and office cost centers by hand. This created delays in month-end close and frequent reconciliation mismatches when employee terminations or department moves were not recorded promptly in CloudSuite. With CloudSuite and Rippling connected, each payroll run's labor journals flow automatically into CloudSuite allocated to the correct project and office, and employee changes sync immediately so the GL dimensions match the active workforce. Month-end close now starts with labor accounts already reconciled, and the manual data entry step is eliminated.

What you can do

• •Sync Rippling employees and departments into Infor CloudSuite as GL dimensions or vendor records for payroll allocation.
• •Post Rippling payroll runs as labor cost journals into CloudSuite's general ledger on your pay schedule, allocated to the correct cost centers.
• •Map Rippling departments and compensation structures to CloudSuite GL accounts and cost centers so payroll entries land on valid dimensions.
• •Handle Infor CloudSuite ION API Gateway OAuth authentication and per-customer base URL configuration, and Rippling OAuth2 or API key auth with polling for employee lifecycle events.
• •Track all records with a full audit trail and replay failed postings without creating duplicates in CloudSuite.

Questions

Which direction does data move between Infor CloudSuite and Rippling?

Employee records and departments flow from Rippling into Infor CloudSuite as GL dimensions or vendor records. Payroll runs are read from Rippling and posted as labor cost journals into CloudSuite's general ledger, allocated to cost centers. Cost centers and GL account mappings are maintained so payroll entries reference valid CloudSuite accounts.

How does the integration handle Infor CloudSuite's per-customer base URL and lack of webhooks?

ml-connector accepts the ION API Gateway base URL and credentials from the customer's .ionapi file, which contains the tenant ID, region, and OAuth endpoints. Because CloudSuite publishes no native webhooks, ml-connector polls the M3 and SyteLine list APIs on a schedule to detect new records and changes, and can also subscribe to ION Desk document flows if the tenant administrator configures them.

How does ml-connector ensure payroll entries are not duplicated when Infor CloudSuite operations are not idempotent?

ml-connector tracks CloudSuite record IDs and invoice numbers created by each payroll post and maintains an external deduplication store. On retry, the system checks this store before creating new entries, and if an entry already exists, it skips the creation and marks the job complete to prevent duplicate postings.