Temporal product knowledge system

AEVORA is an AI-powered platform that transforms scattered project data into organized product knowledge, tracking feature evolution, decisions and history with evidence-backed AI insights.

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Inspiration

In software companies, important product knowledge is scattered across GitHub, Jira, Google Drive, documents and team discussions. When features change or decisions are made, understanding their history becomes difficult. We wanted to solve this problem by creating AEVORA.

What it does

AEVORA (AI-Enabled Evolution & Versioned Organizational Record Architecture) is an AI-powered product knowledge management platform. It collects project information, extracts features and decisions using Google Gemini AI, tracks feature evolution through timelines, and connects historical changes with supporting evidence.

Users can ask questions such as "Why was this feature modified?" and receive evidence-based answers from available project records.

How we built it

We designed AEVORA with a modern web application architecture using React, TypeScript and Tailwind CSS. The backend manages data processing, authentication and integrations. Google Gemini AI helps extract structured information and answer historical questions. Firebase supports authentication and data management, while integrations with GitHub, Jira and Google Drive help connect project information.

Challenges we faced

Some major challenges included extracting meaningful information from different data formats, maintaining feature identity across renames, organizing chronological events, connecting information from multiple sources and ensuring that AI-generated answers are supported by evidence.

What we learned

We learned how AI can transform unstructured project information into organized knowledge, how temporal data models preserve product history, and why security, data consistency and reliable integrations are essential when building intelligent software.

What's next

We aim to improve real-time synchronization, expand integrations, strengthen evidence-based AI responses and make AEVORA a scalable product knowledge platform for organizations.

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Updates

posted an update —

AEVORA has been enhanced with AI-powered document extraction using Google Gemini to identify product features, decisions and historical changes. We have developed product workspaces, feature timelines, knowledge graphs, Recent History and Developer Updates to organize product knowledge. We are improving secure authentication, real-time data synchronization and GitHub, Jira and Google Drive integrations to deliver reliable, evidence-based insights.

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Submission history