How OpenAI uses Clay
OpenAI's RevOps and sales teams use Clay's multi-provider waterfall enrichment to fill gaps in inbound lead data, and its AI research agent to automate account research that sellers used to do manually. Enrichment is also offered to sellers on demand through a Clay package inside Salesforce.
View captured proofThe use case: how OpenAI deploys Clay
OpenAI uses Clay's multi-provider waterfall enrichment to enrich inbound leads, Clay's AI research agent to automate account research that its best sellers did manually, and a Clay package inside Salesforce so sellers can run on-demand enrichment natively in the CRM.
More reported results
Figures published in Clay’s case study. They are not independently measured by usedby.
Maintained consistent weekly usage across sales team members using Clay’s on-demand enrichment Salesforce package, with 8500+ total enrichments run
On busy days, individual sellers may run up to 150 lead enrichments, with especially heavy usage at the start of quarters as teams build pipelines.
In the customer’s words
Clay enables our team to rapidly experiment with trigger driven workflows, and 3rd party enrichment data. We’re able to move fast and drive outsized impact on GTM execution – all while using a tool that’s fun, creative, and cutting edge.With Clay, we more than doubled our enrichment coverage from low 40% to high 80%.Clay was a way to leapfrog us into a multi-source model with the lowest amount of overhead and laborWe see outsized growth potential with Clay.Clay has allowed us to easily leverage multiple providers to scale our inbound lead enrichment process. I've been able to build complex systems that used to require days of data science work now within hours.Clay allows us to move fast and drive outsized impact on GTM execution.Other AI tools used by OpenAI
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Based on Clay’s published case study. We check the public evidence; the results are reported by the vendor.
clay.com- Last checked
- Oct 3, 2026
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Clay's multi-provider waterfall enrichment augmented by OpenAI’s models provided an immediate solution. "With Clay, we more than doubled our enrichment coverage from low 40% to high 80%," Keith notes.