Smart AI Assistant for User Query Resolution Based on Access Control

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Smart AI Assistant for User Query Resolution Based on Access Control

Project Overview

This project involved the development of a Smart AI Assistant leveraging Generative AI technology to address user queries while adhering to strict access control protocols. FeenixAI, an industry leader helping companies accelerate their multi cloud marketplace journey with diverse user roles and data sensitivity levels, required an AI-driven solution to streamline information retrieval and ensure that users only accessed data pertinent to their roles. The AI assistant was designed to provide real-time, accurate responses, enhance productivity, and maintain data security across the organization.

The project scope encompassed the integration of Generative AI capabilities with the existing IT infrastructure, user role definition and access levels, and robust security mechanisms to protect sensitive information.

The Problem

The client faced several challenges that necessitated the development of this AI assistant:

Information Overload: Employees struggled to find relevant information quickly due to the vast amount of data within the organization.

Access Control Issues: Ensuring that users only accessed data they were authorized to see was complex and prone to errors.

Data Security Risks: There was a high risk of data breaches due to improper handling of sensitive information.

The Solution

The solution implemented was a Smart AI Assistant with the following features:

Generative AI Technology: Utilized advanced GenerativeAI Models to understand and respond to user queries accurately.

Role-Based Access Control (RBAC): Integrated RBAC to ensure users only accessed information pertinent to their roles.

Real-Time Query Resolution: Provided instant responses to user queries, significantly reducing wait times.Data Security Protocols: Implemented encryption and secure authentication methods to protect sensitive information.

Information Architecture

The information architecture for the Smart AI Assistant was carefully structured to optimize data retrieval and security:

User Role Hierarchies: Defined clear user roles and associated access levels.

Data Categorization: Organized data into categories based on sensitivity and relevance to different user roles.

Data Encryption: Ensured all data interactions were encrypted to prevent unauthorized access.

Value of the Project

The Smart AI Assistant provided significant value to both users and the organization:

Increased Efficiency: Users could quickly find relevant information, enhancing productivity.

Reduced IT Workload: Automated query resolution reduced the burden on IT support staff.

Enhanced Security: Robust access controls and data security measures mitigated the risk of data breaches.

Compliance: Ensured adherence to data governance policies and audit requirements.

Cost Savings: Reduced reliance on manual IT support led to cost savings for the organization.


The implementation of the Smart AI Assistant significantly improved the efficiency and security of information retrieval within the organization. Users benefited from quick and accurate query resolutions tailored to their roles and the project not only enhanced user satisfaction and productivity but also ensured compliance with stringent data governance policies.

Overall, the success of this project demonstrated the power of AI-driven solutions in enhancing operational efficiency, securing sensitive information, and providing a superior user experience in a corporate environment.

Palo Alto, CA
Technology, Information and Internet.
Amazon Bedrock, Amazon RDS, Amazon Lambda, AWS S3.