AI Clearing vs Scale

AI Clearing connects design and BIM data, schedules, budgets, drone imagery, mobile inputs, and ground surveys into one construction intelligence system for large-scale infrastructure and renewable energy projects. Contractors and asset owners use its CORE platform to see what is actually happening on site instead of relying on scattered spreadsheets and field notes.

A proprietary computer vision engine trained on millions of construction objects compares as-built conditions against design plans. The platform delivers progress and quality reports within 6 to 24 hours of data capture and includes Clara, a conversational assistant that answers project questions from live field data.

Where most construction software tracks tasks in spreadsheets, AI Clearing is built around visual site evidence. It reconciles drone imagery, schedules, and BIM models automatically, which makes it better suited to utility-scale earthworks and renewables than generic project management tools that lack geospatial progress verification.

General contractors, EPC firms, and asset owners working on renewables, transmission, wind, highways, pipelines, railways, and civil earthworks use AI Clearing for progress tracking, quality control, billing verification, and portfolio oversight. Customers include PCL Solar, baywa-re, and Rosendin Renewables.

Scale AI supplies training data, model evaluations, and applied AI systems for labs, enterprises, and governments building machine learning products. The company runs the Scale Data Engine for annotation and RLHF, the GenAI Platform for full-stack generative workflows, and Donovan for defense-oriented intelligence work. Customers include Meta, TIME, Instacart, and public sector agencies that need audited, high-volume data pipelines rather than ad hoc labeling spreadsheets.

Where many labeling vendors focus on a single modality or outsource quality control entirely, Scale combines ML-assisted pre-labeling with layered human review across text, image, video, and 3D sensor fusion including LiDAR. Its Generative AI Data Engine adds prompt generation, red teaming, and benchmark evaluations in one loop, so teams can train, stress-test, and compare frontier models without stitching together separate vendors.

Scale fits ML teams shipping self-driving perception, document NLP, generative assistants, and government programs that demand traceable data provenance. Teams book a demo for custom contracts because pricing is enterprise sales only, not a self-serve checkout page.