gloozd

They think like operators, not engineers. They understood that external calls from customers and internal calls from drivers need different coaching standards. They knew venues need accountability without surveillance. Most importantly, they realized the system only matters if someone actually acts on the insights—so they built the workflow around our team's decision-making, not around the technology itself. That operational mindset made all the difference.

We'd already tried and failed once to build self-service analytics, so the real question wasn't whether gloozd had good tools—it was whether business users would actually adopt them or abandon the system like they did before. Gloozd's answer was a bet on simplicity: BigQuery as the single data layer, Looker's LookML for a unified semantic model, and a drag-and-drop builder plus AI assistant to remove the technical barrier entirely. That foundation made all the difference. Adoption actually stuck because they fixed the underlying problem first—the data architecture and model that had sabotaged us the first time—then built the self-service capabilities on top of solid ground.

Our experience with gloozd was excellent. They fully grasped our vision for creating more than a generic chatbot and delivered a custom AI Barista powered by a specialized coffee knowledge graph. The team was responsive and easy to work with, focused on building a solution that genuinely fits our e-commerce experience. The result is an AI assistant that helps customers discover coffee through relevant, personalized recommendations—the experience of talking to a knowledgeable barista rather than a standard chatbot prone to errors.