Visma and Google Sheets integration

What moves between them

Visma records (suppliers, invoices, POs, GL transactions, dimensions) flow one direction into Google Sheets. ml-connector polls Visma on a schedule tied to your accounting cycle, pulls the changed records via lastModifiedDateTime, transforms them into flat rows matching the customer-defined Sheets schema, and appends or updates rows in the appropriate tabs. Changes to Sheets do not flow back to Visma.

How ml-connector handles it

ml-connector stores Visma OAuth credentials encrypted and manages the client credentials token lifecycle on every poll cycle. For each API call, it injects the required ipp-company-id header using the customer's registered Visma company ID. It maps Visma's native entity structure (nested objects, dimensions, GL account hierarchies) into flat-file rows that fit the customer's Sheets column schema. Because Sheets has no rollback mechanism, ml-connector tracks the last sync timestamp on each tab and skips already-written rows on subsequent runs, preventing duplicates. It handles Visma's rate limit by backing off and retrying, and it handles Sheets API quota by batching writes. Every transaction is logged and can be replayed if a downstream write fails.

A real-world example

A Nordic professional services firm runs Visma.net ERP for accounting and project billing across 50 employees. The finance team exports supplier lists, open invoices, and monthly GL summaries from Visma every week and uploads them to a shared Google Sheet for the operations team to query and reconcile against commitments. With the integration, Visma supplier master, GL accounts, and open invoice lists are live in Sheets, updated on a daily polling schedule. The operations team now sees current open POs and GL postings in Sheets without waiting for exports, and month-end close spreadsheets start from a live snapshot instead of a week-old snapshot.

What you can do

• •Pull suppliers, customers, dimensions, and GL accounts from Visma.net ERP and write them to Google Sheets as master tables.
• •Sync invoices, purchase orders, purchase receipts, and GL transactions on a schedule tied to your accounting cycle.
• •Map Visma OAuth credentials and tenant ID, injecting the required ipp-company-id header on every request.
• •Poll Visma using the lastModifiedDateTime query parameter to avoid re-syncing unchanged records.
• •Enforce a stable column schema across sync cycles and prevent duplicate rows in Sheets.

Questions

Which direction does data move between Visma and Google Sheets?

Data flows one direction: from Visma into Sheets. Visma records (suppliers, invoices, GL transactions, and dimensions) are pulled from Visma and written to Sheets tabs that you define. Changes made in Sheets do not sync back to Visma; Sheets is the reporting layer, not the operational layer.

How does ml-connector handle Visma's OAuth 2.0 and tenant approval requirements?

ml-connector stores the client_id, client_secret, and tenant_id encrypted. On every poll cycle, it obtains a fresh access token via the client_credentials grant against https://connect.visma.com/connect/token. Tenant approval is a one-time setup step with Visma; once approved, ml-connector can access customer data and injects the ipp-company-id header on every request.

Does Google Sheets require a predefined schema, or can customers define their own columns?

Customers define the schema. Before syncing, the customer designs Sheets tabs and column headers (for example, Supplier master: SupplierID, Name, ContactEmail; Invoices: InvoiceID, SupplierID, Amount, DueDate). ml-connector maps Visma fields to those columns and appends rows on each sync. The schema is stable across cycles; ml-connector tracks sync state per tab to avoid duplicates.