Key highlights
40 percent
reduced manual work
30 percent
faster response to user queries
30 percent
enhanced process efficiency
Challenges
The manual extraction process was error-prone, costly, and time-consuming.
Identifying and extracting key entities such as dates, names, and addresses was challenging.
Solution
1.
Extracted key details, such as lease start dates, landlord names, and tenant details, from lease documents using preprocessing modules like optical character recognition (OCR) and text normalization. We handled formats such as PDF and DOCX.
2
Stored the extracted data in an AI-powered database.
3
Employed a Q&A model to understand user needs and generate precise responses by retrieving data from the AI database.
Impact
Lower costs
Faster document extraction reduced time and operational expenses.
Better retrieval
Storing structured data in a database enhanced efficiency and comprehensive analysis.
Higher accuracy
Precise entity extraction improved data integrity and accuracy.