Zenith is a next-generation Work Operating System that integrates artificial intel-
ligence into every layer of the Secure Software Development Life Cycle (SSDLC). Built for engineering teams, it automates planning, task management, communication, code
review, and compliance of all within a unified workspace.
- Problem Statement
- Idea / Solution
- Dependencies
- Setting up a local environment
- Usage
- Technology Stack
- Authors
Modern product and project management processes are complex, involving numerous tasks from UI/UX design to feature implementation and coordination among team members. There's a need to streamline and automate these processes within the Secure Software Development Life Cycle (SSDLC), making project management more efficient and fluid.
Develop an AI-powered Work Operating System as a Software-as-a-Service (SaaS) that provides a common workspace for client company employees. The innovative features of the solution include:
Zenith is a SaaS platform that intelligently integrates team collaboration, code
analysis, and sprint planning with real-time AI support.
• GitHub Bot: Automatically reviews PRs, detects issues, and suggests optimal fixes or alternatives.
• Real-Time Chat Interface: Role-based, secure messaging embedded within the workspace.
• AI Dashboard: Upload documents or files to extract task context, assign story points, and auto-plan sprints.
• Delta Branch Detection: Identifies branch deviations and reassigns story points accordingly.
• AI Canvas: Breaks high-level tasks into subtasks with estimated durations.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
What things you need to install the software and how to install them.
NodeJS - ver. 22.0+
Python - ver. 3.x
A step by step series of examples that tell you how to get a development env running.
First, copy paste this command into any folder (preferably blank):
git clone https://github.com/MashyBasker/inkei.git
Then, you need to create a .env file inside your folder where you have cloned the repository. It will contain GEMINI_API_KEY, MONGO_URI, MONGO_CEO_URI, MONGO_SR_URI, MONGO_JR_URI.
Check .env.exampl for help.
Now copy paste the following code inside your Terminal:
npm i
npm run dev
cd backend -> npm start
You should see https://locahost:5173/ as your frontend server and MongoDB connected and WebSocket server running messages.
Repeat the steps if anything goes wrong.
Now to test the AI pipeline endpoint:
cd AIModels -> cd fuckaround
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt
streamlit run app.py
You should see a streamlit server running at localhost:8501
Supported files - .md, .txt, .rtf
For any discrepancies, reach out to [email protected] :D