Prepare AI-ready infrastructure for faster scaling
and secure operations
Build a governed, AI-ready data foundation for
trusted enterprise decisions
Scale from AI Experiments to decision-grade
enterprise intelligence
Build AI-native apps and automated workflows for seamless, scalable digital experiences.
Create branded content at scale
Enabling enterprise-wide decision Intelligence
CI/CD-ready outputs for seamless deployment
Countries & Territories
Billion Revenue
An enterprise analytics engineering team was managing hundreds of Looker assets manually across projects, models, permissions, roles, folders, and access configurations. As adoption expanded across business domains and environments, manual administration became increasingly difficult to scale and maintain consistently.
Anblicks developed LookerCTL, a Python-based Infrastructure-as-Code framework that uses declarative YAML configurations and the Looker SDK to automate provisioning, validation, deployment, and management of Looker resources. The framework introduced repeatable deployments, centralized configuration, and CI/CD integration, reducing project provisioning from approximately 0.75 FTE of manual effort to less than 5 minutes.
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