Case study

A Customized AI-Powered Web Crawler for PE Firms to Curate an Actionable Target / Investor List

Customized AI-Powered Web Crawler for PE Firms | Case Study

BUSINESS SITUATION

A private equity firm was seeking to automate the search, discovery, and analysis of investor / target businesses, to expedite the screening research, enhance result quality and quantity of targets to have a competitive edge​

ENGAGEMENT

  • The team used our AI-powered web crawler to gather and analyze potential target companies  from an acquisition perspective​
  • We worked with the client to access internal systems and third-party APIs, creating a central  repository of target universe.​


SGA APPROACH

  • Internal data sources: Determined both internal databases / warehouses and external data  sources including third party tools and software systems for comprehensive and robust data  gathering
  • ​External data sources: Aggregated publicly available data from government databases, industry  reports, academic publications, and market research studies​• AI-powered crawler development:
  • ​Developed a scalable web crawler to handle large data volumes from diverse sources​• Integrated AI and machine learning to dynamically navigate and extract relevant information​
  • Created algorithms to parse various web formats and used NLP for contextual data extraction​• Implemented keyword matching and customizable lists for targeted data gathering.​


The tool can help efficiently screen prospects by utilizing a range of apt search criteria and a relevancy score​

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Once targets are shortlisted, the tool will enable deeper insights into specific companies by providing detailed information

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BENEFITS & OUTCOME

  • Efficiency: Saved >50% of screening research time​
  • Better quality of prospects: Resulting prospects lists were broader and of higher  quality compared to existing deal news aggregation tools
  • ​Enhanced business impact: Enabled analysts to focus on higher-level cognitive  analysis, decision-making, and due diligence​

 

KEY TAKEAWAYS

  • Comprehensive analysis, enabling more accurate and informed decision-making​
  • Automated the collection of relevant data, significantly reducing manual effort and  operational costs​
  • Higher return on investment through improved business outcomes​

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