AI Clearing vs RAGnexus

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.

RAGnexus builds private AI assistants for European companies that need answers grounded in their own documents and systems. It connects to the tools where your knowledge already lives, indexes that content into a secure knowledge base, and deploys an assistant your team can query in natural language with cited sources.

The product is designed around data sovereignty. Deployments run on European infrastructure, with options that keep data off third-party model APIs entirely. RAGnexus targets regulated sectors like law, healthcare, and consulting, where confidentiality and GDPR compliance are non-negotiable.

Setup is handled as a managed service. RAGnexus integrates with your existing stack, handles indexing and maintenance, and delivers a working assistant in roughly four weeks for cloud deployments or eight to twelve weeks for fully sovereign on-premises setups.