HackRx 6.0

Build a system that uses Large Language Models (LLMs) to process natural language queries and retrieve relevant information from large unstructured documents such as policy documents, contracts, and emails.

Objective:

The system should take an input query like:
“46-year-old male, knee surgery in Pune, 3-month-old insurance policy”

It must then:

• Parse and structure the query to identify key details such as age, procedure, location, and policy duration.
• Search and retrieve relevant clauses or rules from the provided documents using semantic understanding rather than simple keyword matching.
• Evaluate the retrieved information to determine the correct decision, such as approval status or payout amount, based on the logic defined in the clauses.
• Return a structured JSON response containing: Decision (e.g., approved or rejected), Amount (if applicable), and Justification, including mapping of each decision to the specific clause(s) it was based on.

Requirements:

• Input documents may include PDFs, Word files, or emails.
• The query processing and retrieval must work even if the query is vague, incomplete, or written in plain English.
• The system must be able to explain its decision by referencing the exact clauses used from the source documents.
• The output should be consistent, interpretable, and usable for downstream applications such as claim processing or audit tracking.

Applications:

This system can be applied in domains such as insurance, legal compliance, human resources, and contract management.