Hardening Enterprise Integrations at Scale
Ayan Barua, CEO of Ampersand, on going upmarket with deep native product integrations
The real moat is no longer generating integration code, it is operating that integration reliably across messy enterprise customer environments. Ampersand is built around the part AI does not solve well, which is tenant specific mapping, rate limits, retries, permissions, observability, and ongoing maintenance after the demo works. That is why the value sits in finishing and hardening the workflow, not in producing the first pass of code.
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Ampersand turns per customer integration work into configuration. In the GE style example, the hard part is not calling Salesforce once, it is handling hundreds of tenants, custom objects, different sync rules, and customer specific permissions without creating a new code fork for each account.
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This is the dividing line between native integration infrastructure and unified APIs. Unified APIs flatten systems into a common model, which is useful for standard fields, while Ampersand is aimed at cases where a customer wants its own schema preserved and extended, especially in CRM and ERP deployments.
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The same logic becomes stronger with agents. Agents can help infer mappings and generate manifests, but they still need a control plane for auth, governance, tenancy isolation, retries, and real time reads and writes. That is why integration middleware becomes more important as AI systems take more actions.
Going forward, the winners in integration will look less like connector catalogs and more like reliability infrastructure for agentic software. As AI makes shallow integrations easier to create, the market shifts toward platforms that can keep deep, high consequence workflows correct, fresh, and safe across thousands of customer environments.