AI NLP Model
Case Study

Building a text extraction model to leverage relevant information from various text documents allows classification of document fields and search UI.


AI-based NLP Model for Corporate Strategy

Client lacked the ability to skim through subsections of documents. So, we built a text extraction model, which leveraged relevant information from various text documents to cluster and interpret sections.


Data Sources

  • Scrape the required documents from various online and offline databases
  • Clean-up the data to be in the right format and extract the right set of key words
  • Create vectors based on the right set of similar attributes
  • Leverage algorithms such as Levenshtein distance, cosine similarity to build the final score of the model

Measurable results

  • Meaningful outcome to random text documents
  • Classification of the document fields and a search UI to skim through the sub-sections of documents

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