The National Archives of India houses a vast collection of historical records, offering invaluable glimpses into the nation’s past. However, accessing this information was hampered by a slow and laborious process – manual data entry of information from handwritten Index Registers. This method was not only time-consuming and expensive but also prone to human error.

D-JINN AI, with its custom-built algorithms designed for these intricate records, supercharged the conversion process by a staggering 12 times! A task that once took five years could now be completed in just six months. D-JINN AI deciphered a mix of handwritten text, cursive script, and regional Indian languages alongside printed English with impressive results and extracted the information into a structured database.

D-JINN AI leverages a unique blend of cutting-edge technologies, including Computer Vision, Optical Character Recognition (OCR), Handwritten Text Recognition (HTR), Natural Language Processing (NLP), and Large Language Models (LLMs) to extract, structure and analyze the information trapped within the unstructured data sources, including images, documents, audio, video, and text.

The National Archives’ success story serves as a beacon for other archives struggling with similar challenges. D-JINN AI paves the way for efficient access to historical data, trapped within countless repositories around the world.

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