Ramp engineering leader Arman Vaziri describes go-to-market orchestrationAI go-to-market orchestration coordinates customer data, decisions, automated actions, human tasks, and communication channels around a commercial outcome. as the ability to express a campaign or experiment as intentAn intent-based AI workflow starts from a desired outcome and determines the coordinated tasks needed to reach it., then distribute its execution across outbound, advertising, web and product channels. The goal is to reduce the operational coordination that slows otherwise useful ideas.
Ramp built an internal customer data platformA customer data platform unifies customer information from multiple sources into profiles and datasets that other systems can use. that combines CRM, product, enrichment, web, interaction and buying-signal data. Postgres preserves transactional relationships, warehouse jobs add offline computation, and embedded unstructured information lets agents retrieve only the account context they need.
Vaziri explains how durable Temporal workflowsDurable workflow execution preserves workflow state so long-running processes can survive failures, delays, and restarts without losing progress., scoped tools, human review and reusable skills support specific tasks such as meeting briefs and CRM updates. Ramp then exposes the same foundations through an internal MCP layerModel Context Protocol is an open protocol for connecting AI applications to tools, resources and prompts through a standard interface., allowing employee experiments to reveal new workflows that the engineering team can productionize and distribute more broadly.
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