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Case Study
Explore how our innovative solutions have empowered businesses to overcome challenges and achieve remarkable success.
Explore how our innovative solutions have empowered businesses to overcome challenges and achieve remarkable success.
Built an automated pipeline to continuously collect construction-related content from Gulf region news portals, media sources, and industry publications. This replaced manual article monitoring and created a consistent flow of current project information for further analysis.
Developed an NLP pre-processing layer to clean and tokenise unstructured article content. Word2Vec was used to transform the processed text into semantic vectors, allowing the system to understand contextual meaning even when project information was expressed using different terminology.
Implemented a Logistic Regression classification model to distinguish genuine construction project announcements from general real estate, business, and unrelated media content. Only relevant articles move forward to the extraction process, improving data quality and reducing unnecessary processing.
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Built a specialised extraction engine to automatically identify four critical project attributes from qualifying articles — project location, construction type, expected completion timeline, and project value. This transformed lengthy unstructured articles into concise, usable project intelligence.
Standardised extracted information across different media formats and terminology. Dates were converted into consistent formats, monetary values and currencies were normalised, locations were structured, and project descriptions were mapped into categories such as residential, commercial, infrastructure, hospitality, and industrial.
Integrated the complete pipeline with a structured project intelligence database and REST API, allowing extracted records to feed directly into dashboards, reports, and analytical workflows. Model monitoring and analyst feedback were also incorporated to support retraining as Gulf construction terminology and media patterns evolve.
