Case Study

Mappie AI: From Messy Requirements to Dev-Ready Stories

An AI project management tool I built for Nindo Solutions, live at mappie.ai

Yash Soni · About 1 year from idea to production

The Problem

Backlog grooming is one of the most expensive meetings in software. Senior people spend hours rewriting vague tickets into something an engineer can pick up, and generic LLM chats lack the workflow context to help.

The Solution

Mappie converts vague, unstructured product requirements into clear specifications, epics and user stories. It sits inside the product manager workflow instead of beside it, using context-aware AI to translate a founder idea into tickets.

Architecture & Tech Stack

• Frontend: React, TypeScript, markdown-native editor
• Backend: Node.js
• AI: OpenAI GPT-class models, prompt templates
• Context engine: Document-graph retrieval over the epic and story tree
• Infrastructure: Cloud hosting with CI/CD

Key Features

• Epic and Story Generation: Turns one-line ideas into structured work items
• Context-Aware Chat: AI chat that sees the current epic, story and surrounding docs
• Inline AI Editing: Rewrite, expand or tighten any block without leaving the editor
• Requirements Pipeline: Automated epic to requirements to stories flow with consistent structured output
• Markdown Export: Documentation exports into existing PM tools

Results & Impact

• 60-70% reported reduction in backlog grooming time
• 1,000 beta users
• ~1 yr from idea to production

My Role

I built Mappie AI for the client, Nindo Solutions in Belgium, over close to a year.

Last updated: 2026-10-11