Machine Learning

Our system processed cost items sourced from big company database. A classification model is developed, trained, and validated using advanced machine learning algorithms on the cleaned dataset, ensuring high accuracy and reliability.

• Natural Language Processing (NLP)

  Natural Language Processing (NLP) converts text data into a machine-readable format, making it essential for deep learning architectures. At Veritapp, NLP plays a key role in preparing data for AI models, streamlining the process of transforming unstructured text into structured data ready for building AI models.

• Deep Learning

  Deep neural networks form the core of our system, analyzing text descriptions of cost items in Veritapp. These built-in models automatically classify items into categories such as Plant & Machinery, Special Rate, Structures & Buildings Allowances, Revenue, or Non-Qualifying items, enhancing efficiency and accuracy in item classification.

Statistical Analysis

Historical data collected over time from internal company sources has provided the foundation for building cost models tailored to different property and project types. Statistical analysis is then applied to validate future predictions and identify any outliers, ensuring accuracy and reliability.

• Intelligent Benchmarking System

  Leveraging over 20 years of expertise in capital allowances, we developed a benchmarking system to evaluate AI-generated results. This system monitors the alignment of results with expectations, scoring them based on the value they deliver. Additionally, expert estimations are combined with statistical data from past projects to create reliable, robust benchmarking outcomes. This approach reduces risk and enhances the confidence level of AI-generated reports.

• Cost Breakdown Models

  Classifying items into pools is just the beginning of generating a robust, reliable report. Certain items require further breakdown to maximize allowances. Our system automatically detects items that can be split into more detailed components.These models are built using project specific industry approved building cost data to ensure precise, accurate results.