AI-Driven Investment Advisor App -- 2
Budget: ₹1,500 – ₹12,500 INR
I am looking for an experienced Python developer to build an AI-powered Investment Intelligence Platform for Indian markets.
This is NOT an auto-trading platform.
The platform should act as a professional investment research assistant and provide recommendations, rankings, portfolio insights, risk assessments, alerts and daily reports.
Technology Stack:
- Python
- FastAPI
- PostgreSQL
- Streamlit
- OpenAI API
- Angel One SmartAPI
- TradingView Webhooks
- Telegram Bot
- Docker
Modules Required:
1. Long-Term Investing Engine
2. SIP Recommendation Engine
3. Swing Trading Engine
4. Intraday Trading Engine
5. Commodity Analysis Engine
6. IPO Analysis Engine
7. Portfolio Analysis Engine
8. Risk Management Engine
9. AI Discovery Watchlist Engine
10. Recommendation History Engine
11. AI Accuracy Dashboard
12. Sector Rotation Engine
13. Market Regime Engine
14. Telegram Alert System
15. Morning Executive Report
Data Sources:
- Angel One SmartAPI
- NSE Corporate Announcements
- BSE Corporate Announcements
- Reuters Markets
- Economic Times Markets
- Moneycontrol Markets
- Business Standard Markets
- Investing.com Commodities
- Chittorgarh IPO
Technical Indicators:
- RSI
- MACD
- ATR
- 20 DMA
- 50 DMA
- 200 DMA
- Relative Strength
- Volume Ratio
Dashboard Requirements:
- Market Overview
- Long-Term Recommendations
- Swing Recommendations
- Intraday Recommendations
- Commodity Outlook
- IPO Outlook
- SIP Recommendations
- Portfolio Review
- Risk Dashboard
- News Summary
- AI Discovery Watchlist
- Recommendation History
- Accuracy Dashboard
Requirements:
- Production-ready architecture
- PostgreSQL database
- Docker support
- Logging
- Error handling
- API documentation
- README
- Setup guide
- Full source code ownership
- GitHub repository access
Deliverables:
- Complete source code
- Database schema
- Dashboard
- Docker deployment
- Documentation
- Setup instructions
Please provide:
1. Relevant portfolio/GitHub projects
2. Experience with FastAPI
3. Experience with PostgreSQL
4. Experience with OpenAI API
5. Experience with broker API integrations
6. Estimated timeline
This is NOT an auto-trading platform.
The platform should act as a professional investment research assistant and provide recommendations, rankings, portfolio insights, risk assessments, alerts and daily reports.
Technology Stack:
- Python
- FastAPI
- PostgreSQL
- Streamlit
- OpenAI API
- Angel One SmartAPI
- TradingView Webhooks
- Telegram Bot
- Docker
Modules Required:
1. Long-Term Investing Engine
2. SIP Recommendation Engine
3. Swing Trading Engine
4. Intraday Trading Engine
5. Commodity Analysis Engine
6. IPO Analysis Engine
7. Portfolio Analysis Engine
8. Risk Management Engine
9. AI Discovery Watchlist Engine
10. Recommendation History Engine
11. AI Accuracy Dashboard
12. Sector Rotation Engine
13. Market Regime Engine
14. Telegram Alert System
15. Morning Executive Report
Data Sources:
- Angel One SmartAPI
- NSE Corporate Announcements
- BSE Corporate Announcements
- Reuters Markets
- Economic Times Markets
- Moneycontrol Markets
- Business Standard Markets
- Investing.com Commodities
- Chittorgarh IPO
Technical Indicators:
- RSI
- MACD
- ATR
- 20 DMA
- 50 DMA
- 200 DMA
- Relative Strength
- Volume Ratio
Dashboard Requirements:
- Market Overview
- Long-Term Recommendations
- Swing Recommendations
- Intraday Recommendations
- Commodity Outlook
- IPO Outlook
- SIP Recommendations
- Portfolio Review
- Risk Dashboard
- News Summary
- AI Discovery Watchlist
- Recommendation History
- Accuracy Dashboard
Requirements:
- Production-ready architecture
- PostgreSQL database
- Docker support
- Logging
- Error handling
- API documentation
- README
- Setup guide
- Full source code ownership
- GitHub repository access
Deliverables:
- Complete source code
- Database schema
- Dashboard
- Docker deployment
- Documentation
- Setup instructions
Please provide:
1. Relevant portfolio/GitHub projects
2. Experience with FastAPI
3. Experience with PostgreSQL
4. Experience with OpenAI API
5. Experience with broker API integrations
6. Estimated timeline