Ampersand as Datadog for Sync Infrastructure
Ayan Barua, CEO of Ampersand, on going upmarket with deep native product integrations
The key point is that Ampersand is not just helping teams connect two apps, it is turning a messy, customer specific integration into production infrastructure that can be monitored and operated at scale. In practice, that means a SaaS vendor can let a RevOps team configure object mappings and tenant specific rules, while engineering gets field level logs, rate limit visibility, and error diagnosis instead of maintaining custom code for every big account.
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A concrete example is selling into a company like GE, where one customer can have roughly 170 to 190 Salesforce tenants across countries and regions. The hard part is not connecting once, it is deciding which tenant to read, how often to sync, and how to manage different rules per tenant without creating a permanent services project.
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The Datadog comparison fits because the pain shifts from build time to run time. Once a sync is live, teams need to know whether a broken workflow came from a bad field mapping, lost permissions, an API failure, or a shared Salesforce quota being consumed by another app like Gong. That observability is what keeps enterprise integrations usable after launch.
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This is the clearest difference from unified API vendors like Merge and Finch, and from ETL tools like Fivetran. Merge and Finch simplify access through a common schema, which works best when customers mostly need standard fields. Fivetran moves data into warehouses for analytics. Ampersand is built for transactional product workflows where every customer may want a different schema and deeper write logic.
The market is moving toward integration infrastructure becoming part of the application stack, not a side project for services teams. As more AI and workflow products sell into large enterprises, the winning vendors will be the ones that can promise enterprise grade data movement, monitoring, and customization out of the box, then spend their product time on the workflow itself instead of on plumbing.