A canonical data model + validated pipelines so leadership stops arguing about numbers and starts acting.
Client names withheld by NDA. Details are generalized to protect privacy while preserving the technical and operational shape of the work.
Marketing dashboards didn’t match Finance, definitions drifted across teams, and attribution was disconnected from real pipeline and revenue.
Browse related examples of AI inside revenue systems.
Fit + intent scoring, capacity-aware routing, and decision logs that reduce disputes and speed follow-up.
ReadAutomation that respects region/consent rules and adds AI leverage without polluting the CRM.
ReadNormalization + validation gates so enrichment makes routing/segmentation better—not worse.
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