Sage 300 and Pipedrive integration

What moves between them

Customer records flow one-way from Sage 300 into Pipedrive. ml-connector polls Sage 300's ARCustomers endpoint on a regular schedule, reading customer name, address, contact details, and payment terms. Each customer maps to a Pipedrive organization using the customer ID as the external record key. New customers in Sage 300 trigger new organization creation in Pipedrive; updated customer data triggers an organization update. The sync is additive and non-destructive; Pipedrive organizations not originating from Sage 300 are never modified or deleted.

How ml-connector handles it

ml-connector stores Sage 300 credentials encrypted and constructs Basic Auth headers for every API call, encoding the uppercase username and password as required by Sage 300. It polls ARCustomers using OData filters on the LastModified timestamp to fetch only recently changed records, applying pagination to handle large customer lists. On the Pipedrive side, it uses API token authentication and monitors the daily token budget, backing off if remaining tokens fall below a safety threshold. When creating or updating Pipedrive organizations, it maps Sage 300 customer fields to Pipedrive standard fields and custom field hashes as needed. Customer ID becomes the external record identifier so re-syncing the same customer updates rather than duplicates. Rate limit headers from Pipedrive are parsed to detect per-burst limits and implement exponential backoff before retrying.

A real-world example

A mid-market wholesale distributor runs Sage 300 on-premise for AR and inventory, and Pipedrive on the cloud for sales pipeline and opportunity tracking. The sales team needs current customer data such as credit terms and shipping address in Pipedrive so they can set up deals correctly and avoid overselling to creditworthy accounts. Before the integration, new customer additions in Sage 300 were manually entered into Pipedrive, creating duplicate-entry overhead and risk of stale data in the CRM. With Sage 300 and Pipedrive connected, new customers and address updates from Sage 300 flow into Pipedrive within the poll window, so sales has the current master record without manual re-keying.

What you can do

• •Sync Sage 300 AR customers into Pipedrive organizations on a polling schedule, mapping customer ID as the external record key.
• •Update existing Pipedrive organizations when Sage 300 customer details such as name, address, and payment terms change.
• •Handle Sage 300's HTTP Basic Auth requirement with uppercase-encoded credentials and per-company base URLs.
• •Monitor Pipedrive's daily token budget and rate limits, implementing backoff to stay within plan limits.
• •Maintain a full audit trail of every customer record read from Sage 300 and created or updated in Pipedrive.

Questions

Which direction does data flow between Sage 300 and Pipedrive?

Data flows one-way from Sage 300 into Pipedrive. Customer records are read from Sage 300's ARCustomers endpoint and synced to Pipedrive organizations. Changes in Pipedrive's sales data, deals, and activities do not flow back to Sage 300.

How does ml-connector handle Sage 300's HTTP Basic Auth and uppercase password requirement?

ml-connector encrypts the Sage 300 username and password and constructs HTTP Basic Auth headers for every API call, encoding both credentials in uppercase as required by Sage 300's API. The password must be uppercase in Sage 300's administrative user setup, and ml-connector enforces the same requirement during configuration.

What happens if the polling schedule misses a changed customer or Pipedrive hits its daily token limit?

ml-connector tracks the LastModified timestamp on each poll cycle and resumes from that point on the next run, so changed customers are not missed. If Pipedrive's daily token budget approaches its limit, ml-connector backs off and pauses new syncs until the budget resets, preserving tokens for critical operations and resuming when the daily window rolls over.