Challenge

Printers joining Gelato’s network had to manually map as many as 200,000 SKUs, a task that previously took 9–24 months and often stalled, costing both sides revenue. Internally, adding new logistics carriers required days of engineering effort, slowing global expansion. ​
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Background Context

With 250 staff spread across 50 countries, Gelato set out to scale its “produce‑locally, sell‑globally” platform without linearly expanding headcount. The product team saw multi‑agent AI as the lever to remove manual bottlenecks and let each employee—and customer—do more, faster. ​

CrewAI’s agent framework could plug into Gelato Connect, automating heavy data‑mapping and integration work while remaining invisible to end‑users—freeing engineers to focus on value‑added features and helping customers close new business sooner.
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Implementation Overview

• Embedded thousands of CrewAI agents behind the scenes of Gelato Connect to auto‑map bulk product catalogs and validate file uploads.
• Deployed logistics agents that generate, test, and deploy carrier‑integration code, shrinking onboarding from 5 days to 10 minutes.
• Rolled out internal “Crews” for routine ops tasks, multiplying individual productivity. ​

Early agent deployments slashed SKU‑mapping timelines by >90 % and cut carrier‑integration effort by ~99 %, enabling printers to accept new customers sooner and Gelato to accelerate global coverage—all without proportional increases in headcount. ​