Project Cost Estimation

AI automates semantic alignment of quantity take-offs with cost indexes for accurate estimation

Business impact

• Cost Estimation Accuracy — AI reduces errors by automating alignment between quantity take-offs and cost data
• Estimation Time — Automation significantly decreases time required for generating cost estimates
• Financial Risk — Improved accuracy lowers risk of budget overruns and financial losses
• Operational Efficiency — Streamlined workflows reduce manual effort and improve resource allocation

Data requirements

• Quantity Take-Off (QTO) descriptions (Text) — Textual descriptions of measured building components used for cost matching
• Construction Cost Indexes (CCIs) (Structured) — Structured cost data with classified work items and unit rates for alignment
• Building Information Modeling (BIM) models (Structured) — 3D parametric models providing quantities and attributes for estimation

AI methods and techniques

• Predictive AI — Used to forecast cost estimates based on historical and real-time data patterns
• Generative AI — Employed in natural language processing to interpret and align textual descriptions
• Symbolic AI — Applied for rule-based text normalization and classification in preprocessing

AI models and model families

BERT, spaCy, Word2Vec, GloVe, Ensemble NLP models

Industries

Real-world evidence

7 documented case studies on record.

Companies using this: Australian Institute Quantity Surveyors AIQS, Carroll Estimating, Cast Consultancy, DPR Construction, Duck Creek Technologies, Trimble, Windover Construction.