FreshBooks and Dayforce integration

What moves between them

The main flow is Dayforce into FreshBooks. Employee names, roles, and cost allocations flow from Dayforce to FreshBooks so labor expenses can be assigned to the correct client and GL account. Org units and positions in Dayforce map to departments and expense categories in FreshBooks. The sync runs on a schedule tied to your payroll cycles; ml-connector fetches changed employees and org units from Dayforce since the last sync and updates or creates matching records in FreshBooks, then marks those expenses for allocation to the correct client and GL account.

How ml-connector handles it

FreshBooks uses user-delegated OAuth tokens that ml-connector stores encrypted and refreshes on demand. Dayforce uses Resource Owner Password Credentials (ROPC) and returns one-hour bearer tokens that expire quickly, so ml-connector requests a fresh token before each sync cycle and caches it for the duration of that cycle. Dayforce requires a client-specific base URL retrieved from /V1/ClientMetadata; ml-connector refreshes this daily to avoid redirect overhead. On each sync, ml-connector queries Dayforce employees and org units with a time-range filter to fetch only records changed since the last run, then maps Dayforce positions to FreshBooks expense categories and Dayforce org units to FreshBooks chart of accounts segments. FreshBooks webhook signatures are validated on incoming events using HMAC-SHA256. Payroll cost allocations are added to FreshBooks journal entries with the mapped GL account and client reference. Every record carries an audit trail and can be replayed if a downstream write fails.

A real-world example

A mid-sized professional services firm runs FreshBooks for invoicing and expense tracking, and uses Dayforce for payroll and employee management across three offices. Before the integration, the accounting team received the monthly payroll register from Dayforce and manually re-entered labor expenses into FreshBooks by employee and office, mapping each person's pay to the correct client project and GL account. This took several hours each month and introduced errors when employees moved between projects or offices. With FreshBooks and Dayforce connected, employee data flows automatically from Dayforce into FreshBooks, and labor allocations are applied to the correct client and GL account each pay cycle. Month-end expense reconciliation is faster because the payroll and client data are already in sync.

What you can do

• •Sync Dayforce employee names, roles, and cost center assignments into FreshBooks so labor expenses can be allocated to the correct client and GL account.
• •Map Dayforce org units and positions to FreshBooks expense categories and chart of accounts to keep cost allocations consistent with your org structure.
• •Refresh Dayforce tokens hourly to maintain a live connection without manual intervention or outages.
• •Poll for changed employees and org units on a payroll-aligned schedule, with retries and a full audit trail on every record.
• •Track which labor expenses have been allocated to clients and GL accounts, with replay capability if a downstream write fails.

Questions

What direction does employee and cost data flow between FreshBooks and Dayforce?

The main flow is Dayforce into FreshBooks. Employee names, roles, and cost center assignments flow from Dayforce to FreshBooks so labor expenses can be assigned to the correct client and GL account. Org units and positions in Dayforce map to departments and expense categories in FreshBooks. FreshBooks is the target system where allocations are applied.

How does ml-connector handle Dayforce's one-hour token expiry and client-specific API URL?

Dayforce bearer tokens expire in one hour, so ml-connector requests a fresh token before each sync cycle and caches it for the duration of that cycle. Dayforce publishes a client-specific base URL that must be refreshed daily from /V1/ClientMetadata to avoid redirect overhead; ml-connector fetches and caches this URL at the start of each day.

How does the integration find which Dayforce records have changed since the last sync?

Dayforce is pull-only with no native webhooks, so ml-connector polls for changed records using filterUpdateDateRangeMin and filterUpdateDateRangeMax query parameters on the employees and org units endpoints. Each sync passes the time range since the last run, so only modified records are fetched, reducing API calls and sync time.