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Interactive NLP Chatbot for Accelerating Internal Operations

nix-united.com

Medical

Information technology

Business Challenges

Employees face significant time consumption in manually reviewing system update documentation, leading to reduced operational efficiency and performance. The lack of an efficient information retrieval system hampers productivity and diverts resources from high-value tasks.

About the Client

Multinational corporation providing healthcare information technology solutions and clinical research services

Project Goals

Develop a question-answering machine learning algorithm for accurate information retrieval
Create a cross-platform chatbot (web, mobile, desktop) with conversational AI capabilities
Ensure seamless integration with the client's internal systems and documentation repositories

Core Functional Requirements

Natural Language Processing (NLP) engine with BERT-based text classification
Multi-platform chatbot interface with 80%+ accuracy threshold for responses
Interactive feedback mechanism for continuous model improvement
Automated HTML document parsing and contextual structure preservation module
Azure Bot Framework integration with containerized deployment

Technology Stack

TensorFlow

PyTorch

BERT QA

Azure Bot Framework

Azure DevOps

System Integrations

Client's internal documentation system
Azure Container Instances
Microsoft Bot Framework services

Non-Functional Requirements

Scalable cloud architecture on Azure platform
99.9% system reliability SLA
Real-time response processing under 2 seconds
Enterprise-grade data security and compliance
Adaptive learning capabilities for model improvement

Business Impact

Implementation of the AI-powered chatbot is expected to reduce employee information retrieval time by 60-70%, enabling reallocation of resources to high-value activities. The solution will enhance operational efficiency through automated document processing and improve knowledge management across global teams.