As Digs introduced new AI capabilities, its data annotation needs became more sophisticated. Work that began with room segmentation expanded into room naming, measurements, wall interpretation, and other blueprint elements. The challenge was not simply labeling more images. Digs needed a data annotation operation capable of adapting as the product evolved while also preserving downstream consistency builders and homeowners depended on.

Finding an annotation partner that could adapt as the product evolved

Digs partnered with Uber AI Solutions (UAIS). The UAIS team quickly aligned with Digs’ existing technical environment and evolving workflows, rather than forcing them into a rigid operational structure. UAIS assembled a dedicated annotation team and worked within Digs’ established review process. As requirements changed, workflows were adjusted incrementally. Adjusted workflows supported rotated layouts, updated segmentation rules, room naming, measurements, and increasingly specialized blueprint elements without rebuilding the operation from scratch.

The collaboration also addressed an operational visibility gap. Because review and ingestion processes existed across separate systems, blocked work and emerging issues could be difficult to identify quickly. UAIS introduced dashboard reporting and automated Slack updates that surfaced queue status, active operations, and blocked items, giving both teams greater day-to-day visibility while reducing manual coordination.

بفضل الخبرة التشغيلية في إدارة برامج التعليم المعقدة والقدرة على التكيف مع المتطلبات المتغيرة، مكّن نظام UAIS شركة Digs من توسيع استخدام بيانات البناء المنظمة دون الحاجة إلى إنشاء عملية داخلية جديدة في كل مرة تتغير فيها متطلبات التعليم.

A scalable foundation for AI-powered construction workflows

AI systems for residential construction depend on accurate interpretation of highly variable visual documents. Building those capabilities requires annotation operations that can evolve alongside the product itself.

By partnering with Uber AI Solutions, Digs established a reliable blueprint annotation workflow capable of supporting changing requirements, maintaining quality, and scaling operationally without introducing unnecessary complexity. Now, Digs is building AI-powered workflows for the modern era of home construction and ownership.