Data science solution to extract and rationalise requirements of nuclear projects

Deployment of DeepREXT solution (Advanced Natural Language Processing methods able to capture custom semantics):

• Phase 1: Requirements extraction
  
  • Detect and extract requirements from a raw technical documentary
• Phase 2: Requirements classification
  
  • Train the model to classify the extracted requirements according to a precise classification map given by the customer
  • Automate the classification of requirements
• Phase 3: Requirements rationalization
  
  • Automate the comparison of sets of requirements that have been produced by different entities to identify duplicated and inconsistent requirements

• Time savings through accelerating by at least 50% the transformation of requirements gathered from raw documents into a unified format thanks to automation of requirements extraction
• Time savings (no need to write custom rules) thanks to the training on thousands of labelled examples, enabling the models to be capable of capturing all necessary dependencies
• Smarter algorithms thanks to collection of feedback from engineers to adjust models (in particular feedback of requirements classification and extraction)
• Good understanding of various styles of writing of the different authors thanks to the flexibility of DeepREXT enabling to understand the underlying meaning of words of all requirements