AI-powered benefits document assistant

Overview

Benefits documents are notoriously complex. Employees often spend hours parsing through dense, jargon-heavy materials just to understand basic coverage questions. BenefitsGuru was built to solve this problem.

The platform allows users to upload their benefits documents—PDFs, Word files, PowerPoints, or Excel sheets—and ask questions in natural language. The AI processes documents of any length, from 10 to 100+ pages, and returns concise, accurate answers in seconds.

The challenge

The client needed a system that could:

• Process multiple document formats with varying structures
• Provide accurate answers without hallucination
• Support voice input for accessibility
• Handle queries in 80+ languages and dialects
• Scale to handle concurrent users efficiently

What we built

We implemented a robust document processing pipeline using semantic chunking and hybrid search (BM25 + vector embeddings). Documents are processed asynchronously through Celery workers, with chunks stored in Elasticsearch for fast retrieval.

The AI layer uses retrieval-augmented generation (RAG) to ground responses in the actual document content, minimizing hallucination. We also integrated a knowledge base of government regulations to provide comprehensive answers.