AI-Powered DORA Metrics Explorer

Organization: Personal Project

Location: India

Project Type: Individual

Duration: Jun 2025

Role: AI/ML Engineer

Project Description

Developing a web apps prototype using LLM-RAG architecture to analyze DORA metrics and provide actionable insights for stakeholders. This tool is expected to process DORA metrics including deployment frequency, lead time, change failure rate, and time to restore service metrics to support analysis, to identify bottlenecks and improvement opportunities. It uses a sophisticated RAG system to provide context-aware recommendations based on industry best practices and historical data.

Detailed Tasks

Designed a web app prototype using Python and Flask to provide a user-friendly interface for analyzing DORA metrics. Enable natural language input and display of LLM-generated insights
Implemented a basic RAG-based architecture for processing and analyzing DORA metrics

Detailed Tasks (expected to be completed)

Design and implement a full fledged RAG-based architecture for processing and analyzing DORA metrics and generating context-aware recommendations
Develop custom embeddings for technical documentation and best practices
Create an automated data pipeline for collecting and processing metrics from various sources
Implement a recommendation engine using LLM for generating actionable insights

Core Skills

Gen AI

Large Language Models

Prompt Engineering

Machine Learning

Data Science

Retrieval Augmented Generation

LLM Development

RAG Architecture

Data Pipeline Development

Performance Optimization

CI/CD Integration

Dashboard Development

Tech Stack

Frontend

HTML5
CSS3
Bootstrap

Backend

Python
Flask
Flask Sessions

Data & ML

Pandas
CSV Processing
Matplotlib
Scikit-learn

LLM & Models

Ollama
LLaMA 3
Sentence Transformers
RAG Architecture
Context-Aware Processing
Vector Embeddings

Deployment

Flask Web App
Render
Railway

Business Impact

Expected reduction in analysis time by 60% through automated DORA metrics processing
Enabled natural language data-driven decision making with context-aware insights and recommendations

Expected Project Outcome

Enhanced accuracy and efficiency in DORA metrics analysis through advanced LLM and RAG techniques.
Improved decision-making capabilities for stakeholders by providing actionable insights derived from complex data sets.

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