Selecting the right service provider is a challenging process for businesses, especially when requirements are documented in unstructured formats such as scanned files, PDFs, or handwritten documents. Traditional lead generation relies on manual document review and extensive market research, making the process time-consuming and prone to human error. To address this challenge, this work proposes an automated business lead generation system that integrates Optical Character Recognition (OCR) with a structured provider database derived from Crunchbase. The system enables users to upload requirement documents, which are then converted into machine-readable text using OCR. The extracted text is analyzed to identify key service requirements, operational needs, and domain-related terms. These processed details are matched with a curated database of service providers to generate a ranked list of the most suitable companies. The proposed system reduces manual effort, accelerates decision making, and provides accurate, document-driven lead recommendations. Overall, the solution demonstrates an intelligent and scalable approach to automating vendor identification using document analysis and database-driven matching.