System Requirements Document for cosmic-want

1. Introduction

The project "cosmic-want" aims to develop an AI Organizational Memory Engine that addresses the challenge of knowledge loss within companies. This system will create a dynamic and evolving knowledge graph, termed as the "Organizational Digital Brain," by continuously analyzing various data sources within an organization.

2. System Overview

The "cosmic-want" project seeks to build an AI system that constructs a living knowledge graph of an organization by integrating and analyzing data from emails, Slack, Jira, GitHub, documents, meetings, and pull requests. The system will learn and track expertise, dependencies, decision-making processes, changes, approvals, and project evolution.

3. Functional Requirements as Story Points

• As a System, I should be able to read and analyze emails to extract relevant knowledge.
• As a System, I should be able to integrate with Slack to capture and analyze conversations.
• As a System, I should be able to access Jira to understand project tickets and their status.
• As a System, I should be able to connect with GitHub to track code changes and pull requests.
• As a System, I should be able to process documents to extract and update organizational knowledge.
• As a System, I should be able to capture and analyze meeting notes to understand decisions made.
• As a System, I should be able to learn and identify who knows what within the organization.
• As a System, I should be able to understand which APIs depend on others.
• As a System, I should be able to track why decisions were made and what changed.
• As a System, I should be able to identify who approved changes and track project evolution.

4. User Personas

• Admin: Responsible for managing system configurations and integrations.
• Employee: Uses the system to access and contribute to the organizational knowledge base.
• Project Manager: Utilizes the system to track project evolution and decision-making processes.

5. Core User Flows

• Admin sets up integrations with email, Slack, Jira, GitHub, and document repositories.
• Employee accesses the system to retrieve information about project dependencies and expertise.
• Project Manager reviews the knowledge graph to understand project evolution and decision-making.

6. Visuals Colors and Theme

[Default — not specified by user]

• primary: #1E90FF (Dodger Blue)
• primary_light: #63B8FF (Light Dodger Blue)
• secondary: #FFD700 (Gold)
• accent: #FF4500 (Orange Red)
• highlight: #32CD32 (Lime Green)
• bg: #F5F5F5 (White Smoke)
• surface: #FFFFFF (White)
• text: #333333 (Dark Gray)
• text_muted: #777777 (Gray)
• border: #DDDDDD (Light Gray)

7. Signature Design Concept

The homepage of "cosmic-want" will feature an interactive galaxy map where each star represents a different data source or knowledge node. Users can click on a star to open a detailed view of the information it holds, drag to rotate the galaxy, and hover to highlight connections between nodes. This concept will be implemented using @react-three/fiber and @react-three/drei for a 3D interactive experience.

LANDING HERO MOTION BRIEF

The landing page will feature a continuously moving 2D composition where data streams (emails, Slack messages, Jira tickets) flow into a central "brain" icon, which then lights up to represent the creation of new knowledge. This animation will be built using motion/react and CSS for smooth transitions and will loop every 10 seconds to maintain user engagement.

8. Interaction Model & Motion Direction

• Intended Interaction Model: Animated
• The landing page will feature moderate scroll-triggered reveals and hover transitions to enhance user interaction and engagement.

9. Non-Functional Requirements

• The system must ensure data privacy and comply with relevant data protection regulations.
• The system should be scalable to handle large volumes of data from multiple sources.
• The system must provide real-time updates to the knowledge graph.

10. Tech Stack

• Frontend: React for Web
• Backend: Python, FastAPI
• Database: MongoDB for NoSQL storage
• AI Models: GPT 5.4 for user-friendly responses
• AI Tools: Litellm for LLM Routing, Langchain
• Local Orchestration: Docker, docker-compose
• Server-side Orchestration: Kubernetes

11. Assumptions and Constraints

• The system assumes access to all necessary data sources within the organization.
• The system must operate within the constraints of existing IT infrastructure and security policies.

12. Glossary

• LLM: Large Language Model
• API: Application Programming Interface
• PR: Pull Request
• RAG: Retrieval-Augmented Generation