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The Aadhaar Card Is One Of The Most Widely Used Identification Documents In India, Containing Essential Demographic Details And A Unique 12-digit Identification Number. With The Rapid Digitalization Of Services, Automating The Extraction Of Aadhaar Card Information Has Become A Critical Requirement For Various Applications Such As E-KYC, Digital Onboarding, And Identity Verification. This Project Aims To Develop A Web-based Application That Extracts Aadhaar Card Details And The Profile Image Using Optical Character Recognition (OCR) And Haarcascade-based Face Detection Techniques. The System Utilizes OCR To Identify And Extract Textual Information Such As The Aadhaar Number, Name, Date Of Birth, Gender, And Address Directly From The Scanned Or Uploaded Aadhaar Card Image. Simultaneously, Haarcascade, A Machine Learning-based Object Detection Algorithm, Is Employed To Detect And Extract The Profile Image From The Card. The Extracted Details Are Then Structured And Displayed On The Webpage For Further Use In Authentication Or Record Management. This Approach Minimizes Manual Data Entry, Reduces Human Error, And Accelerates Digital Onboarding Processes. The Integration Of OCR And Haarcascade Ensures Efficient Extraction Of Both Textual And Image Components, Making The System Reliable, Scalable, And Suitable For Real-world Identity Verification Applications.