Sage Intacct and Google Sheets integration

What moves between them

Vendors, AP bills, and GL accounts flow from Sage Intacct into Google Sheets on a schedule you define, typically daily or weekly. ml-connector reads from Sage Intacct, transforms each record to match the column headers in your target sheet, and writes the rows. If a write to Google Sheets fails or is interrupted, the full record set is replayed on the next sync. AP payments and GL dimensions can be included if your sheet includes them. The flow is one-way: Sage Intacct is the source of truth, and your sheet is kept in sync.

How ml-connector handles it

ml-connector stores your Sage Intacct credentials (senderId, companyId, userId) encrypted and uses them to obtain a session on the first call. The session is cached in-process and refreshed automatically 5 minutes before its 50-minute expiry, so subsequent calls reuse the session without re-authenticating. For Google Sheets, ml-connector uses either OAuth 2.0 user delegation or a Service Account, depending on your setup. On each sync run, ml-connector queries the target sheet to read the column headers, then fetches vendors, AP bills, and other configured entities from Sage Intacct's XML gateway. Each record is mapped to the columns in your sheet, and rows are appended or updated using Google Sheets' batchUpdate operation. If the Google Sheets write fails (rate limit, timeout, or permission issue), the job is queued for replay with exponential backoff. Sage Intacct's XML responses are parsed for application-level errors even on HTTP 200, so failures are caught and handled correctly. Every sync run is logged with a full audit trail, including record counts, timestamps, and any errors encountered.

A real-world example

A mid-size professional services firm uses Sage Intacct for accounting and vendor management. The finance team works largely in spreadsheets for month-end close, invoicing analysis, and vendor reports. Before the integration, the accounting manager exported vendor lists and AP registers from Sage Intacct as CSV files, pasted them into shared Google Sheets, and manually updated vendor columns when changes occurred. The process was error-prone and created delays during vendor onboarding and payment reconciliation. With Sage Intacct and Google Sheets connected, the vendor master and AP bill records sync automatically each morning, so the finance team's spreadsheets always reflect the latest Sage Intacct data. The team can now focus on analysis instead of data entry, and the audit trail shows exactly when each record was synced.

What you can do

• •Sync vendor master data from Sage Intacct into Google Sheets automatically on a schedule.
• •Write AP bills and AP payments into your sheet with full GL account and dimension mappings.
• •Automatically refresh Sage Intacct session credentials before they expire, with no manual intervention.
• •Detect and log application-level errors in Sage Intacct XML responses, even when HTTP status is 200.
• •Replay failed Google Sheets writes with exponential backoff and maintain a complete audit trail of every sync run.

Questions

Does ml-connector support Sage Intacct's session expiry and automatic refresh?

Yes. Sage Intacct sessions expire after 50 minutes. ml-connector caches the session and automatically refreshes it 5 minutes before expiry, so you do not have to re-enter credentials or monitor session age. If a call is made after expiry, ml-connector obtains a new session transparently.

How does ml-connector handle the schema in Google Sheets?

Google Sheets has no pre-built ERP structure, so your team defines it by creating sheet tabs and column headers. ml-connector reads the header row on each sync, maps each Sage Intacct field to the matching column, and appends or updates rows. If a column in your sheet does not match a field from Sage Intacct, ml-connector skips it or fills it with empty values, depending on your mapping.

What happens if a write to Google Sheets fails mid-sync?

ml-connector queues the failed sync for replay with exponential backoff. The next scheduled run will retry the same records. Every attempt is logged in the audit trail, so you can see which records succeeded, which failed, and when the retry completed.