Artificial Intelligence (AI), Machine Learning, Software Engineering, Process Automation

Ongoing

SDLC Automator

DAKDMentor 1: Prof. (Dr.) Amit Kumar Das

BCMentor 2: Biswajit Chaki

MJBLead: Jigisha Basu

Team: Agentic Team

Started: 4/1/2025

Project Overview

This project introduces an AI-powered SDLC Automation Studio that revolutionizes software development documentation. By leveraging multi-agent AI (CrewAI + LLMs), the system automates creation of all major SDLC artifacts—BRDs, SRS, SDD, test plans, and deployment documents—delivering results in hours instead of weeks.

Methodology

Multi-agent collaboration simulating analyst, architect, developer, tester roles
Automated document generation from RFPs, BRDs, or user stories
Cloud-native processing for scalability and accessibility
Template-driven consistency aligned with industry standards

Key Results & Findings

90% reduction in documentation time
Standardized, high-quality artifacts without manual rework
Seamless integration with Jira, GitHub, Confluence
Cloud-based for collaboration and scalability

Performance Metrics

Challenges & Solutions

Handling complex domain-specific documentation - Agentic AI agents specialized for roles (BA, Architect, Developer, QA)
Maintaining consistency across documents - Template-driven, LLM-powered generation

Future Work

Integration with DevOps pipelines
Multi-language support for global teams
Expansion to automated compliance documentation

Project Information

Duration

4/1/2025 - Ongoing

Team Members

Agentic Team

Use Cases

✨

SRS

✨

SDD

✨

Proposal

✨

Test Cases

Project Milestones

Requirement Analysis100%

System Design85%

AI Model Development70%

Testing & Validation45%

Documentation & Deployment20%