AnuShakti AI – QA Assignment

This repository contains the QA testing work performed for the AnuShakti AI application, an AI-powered technical assistant for the Atomic Energy Regulatory Board (AERB) documents.

📌 Project Overview

AnuShakti AI helps users retrieve information from AERB publications with:

• Accurate answers with source citations
• Non-hallucination behavior
• Handling of text, numerical, and image-based queries

📌 Repository Contents

• Test_Scenarios/ – Top 3 critical test scenarios identified for production readiness
• Test_Cases/ – Detailed test cases including edge cases, test data, expected & actual results, and execution status
• Defect_Reports/ – Logged defects with clear steps to reproduce, expected vs actual behavior, severity & priority
• Test_Summary/ – 1-page summary covering key risks, overall quality assessment, release recommendation, and known gaps
• Screenshots/ – Relevant screenshots from test execution (errors, outputs, etc.)

📌 Links to Documents

• Test Scenarios & Detailed Test Cases (Execution Status): Click me
• Bug Report: Click me
• Test Summary Report (PDF/Doc): Click me
• Screenshots: Click me

📌 Key Highlights

• Focused on core product functionality and risk-based testing
• Executed edge cases and failure scenarios to validate stability and performance
• Documented release-blocking defects with clear reproduction steps
• Followed real QA documentation standards and structured deliverables

📌 Author

Paras Kumar Zambarlal Sanghvi
QA Engineer