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Case study · Construction and sustainability

From construction documents to a robust sustainability analysis

ANNAGH AI reads project documents, checks them against a broad criteria catalogue and creates a source-based one-pager. Experts add missing information and review the result over several iterations.

800+ pages of standards · Project documents · Human in the loop

Langacker L71 residential development in Ruggell

Many documents, many criteria, little time

Sustainability data is distributed across specifications, offers, material lists and plans. Manual review takes substantial expert time and can still miss relevant information.

How the solution works

  • Google AI processed more than 800 pages of standards and technical sources to build a residential construction criteria catalogue.
  • The application evaluates energy, materials, circularity, health and innovation using quantitative and qualitative evidence.
  • Material quantities are read from actual consumption tables and used to recalculate CO₂ values.
  • When information is missing, the AI asks targeted questions. The site manager adds or corrects data in an iterative review.

The result

An exportable one-pager presents the score, categories, strengths and major CO₂ drivers. References link every statement back to a document and page.

Clear boundary

The AI score is a well-founded estimate based on a broad information base. CO₂ values are calculated from recorded material quantities. The analysis still does not replace a certified life-cycle assessment or formal proof of standards compliance.

Would you like to implement a similar use case? We will help define the right first step.