GenVis is an AI-driven productivity tool built for Product Managers to transform raw ideas into actionable plans, structured requirements, and automated sprint reports fully integrated with Jira and Slack.
Originally built for PNC Bank’s Product Innovation Challenge at HackUTD 2025, GenVis accelerates the product lifecycle from Ideation → Planning → Reporting, while meeting the following two HackUTD challenges:
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- Generate product ideas, pain points, and customer personas with Nemotron AI-powered brainstorming.
- Convert insights directly into structured project requirements.
- Automatically generate user stories and acceptance criteria.
- Instantly push tasks to Jira for sprint planning.
- Summarize project progress and generate stakeholder updates.
- Automatically broadcast reports to Slack channels.
- NVIDIA Nemotron for AI reasoning and generation.
- Jira REST API for backlog sync.
- Slack Incoming Webhooks for reports.
- API responses and AI outputs are cached temporarily.
- Cached items are timestamped to show when each system was last used.
| Layer | Technology |
|---|---|
| Frontend | React, JavaScript, HTML/CSS, Lucide Icons |
| Backend | FastAPI (Python) |
| AI Model | NVIDIA Nemotron-Nano-9B |
| Integration | Jira REST API, Slack Webhooks |
| Environment | Python 3.9+ with venv |
| Hosting (planned) | AWS / Render / GCP |
Run the following commands in your terminal:
git clone https://github.com/razeenr05/GenVis.git
cd GenVisSet up the backend environment and install dependencies:
cd backend
python3 -m venv venv
source venv/bin/activate # Mac/Linux
venv\Scripts\activate # Windows
pip install -r requirements.txtCreate backend/.env from .env.example and configure your keys from the respective websites:
# Nemotron
NVIDIA_API_KEY=your_nvidia_api_key
NVIDIA_MODEL=nvidia/nemotron-nano-9b-v2
# Jira
JIRA_BASE_URL=https://yourworkspace.atlassian.net
JIRA_EMAIL=[email protected]
JIRA_API_TOKEN=your_jira_api_token
JIRA_PROJECT_KEY=PROJECT
JIRA_ISSUE_TYPE=Story
JIRA_STORY_POINTS_FIELD=customfield_10020
# Slack
SLACK_WEBHOOK_URL=https://hooks.slack.com/services/XXX/YYY/ZZZ
SLACK_CHANNEL=#product-updates
PORT=8000
HOST=0.0.0.0Run the backend:
uvicorn mock_api:app --reloadSet up the frontend and start the app:
cd ../frontend
npm install
npm startOpen the app at http://localhost:3000.
GenVis/
├── backend/
│ ├── agent_backend.py # Core agent workflows, Nemotron orchestration
│ ├── integrations.py # Jira + Slack helper functions
│ ├── mock_api.py # FastAPI application & routes
│ ├── requirements.txt # Python dependencies
│ └── .env.example # Sample environment variables
│
├── frontend/
│ ├── public/
│ │ └── index.html # Frontend HTML entry point
│ ├── src/
│ │ ├── App.js # Main React application
│ │ ├── App.css # Global styling
│ │ ├── index.js # React DOM entry
│ │ ├── index.css # Reset & global CSS
│ │ └── assets/ # Images, icons, and static assets
│ └── package.json # Node dependencies & scripts
│
├── .gitignore
└── README.md
- Deploy to cloud infrastructure (Render / AWS / GCP) (For easy use)
- Build analytics dashboards for AI insights and sprint metrics
- Enhance Slack bot with two way communication
- Further fine tune the AI responses
- Use PostgreSQL to permanently log use times (Helps know when tasks are being created or done)
GenVis helps with product ideation, requirement drafting, and executive reporting by connecting AI generated insights directly to enterprise tools like Jira and Slack. Initially tailored for PNC’s product workflow, GenVis scales to any organization seeking AI-assisted product delivery, to help with workflow and save time on short-term tasks.
- Isaac Pandyan
- Krish Patel
- Razeen Rahman