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Gainful - AI Quant Advisor Platform

A scalable web platform enabling users to create their own custom agentic quant advisors using fine-tuned LLMs and custom ML pipelines for stock price prediction.

React Redux Toolkit LangChain LangGraph FastAPI PyTorch LSTM Transformer
Gainful - AI Quant Advisor Platform

Project Overview

Gainful is a cutting-edge platform that democratizes quantitative trading by allowing users to create personalized AI-powered investment advisors. The platform combines modern web development with advanced machine learning techniques.

Key Features

  • Custom Agent Creation: Users can build their own quant advisors tailored to their investment strategies
  • ML-Powered Predictions: Multiple model architectures for stock price prediction
  • Natural Language Interface: Chat with your advisor using plain English
  • Real-time Analysis: Live market data integration and sentiment analysis

Technical Implementation

Frontend

Built an easy-to-use, accessible UI using React, SCSS, Redux Toolkit, and Jest for comprehensive testing.

Machine Learning Pipelines

Created, trained, and back-tested custom ML pipelines for stock price prediction:

  • LSTM Networks: For sequential time-series analysis
  • Hybrid Transformer: Attention-based architecture for capturing long-range dependencies
  • Hybrid Ensemble: Combining LSTM, XGBoost, Random Forest, and LightGBM for robust predictions

AI/NLP Layer

Prompt-engineered and fine-tuned Llama 2 70B and BERT models to:

  • Gather user intention through natural conversation
  • Generate news sentiment analysis
  • Create and configure new trading agents dynamically

Built using LangChain and LangGraph for agent orchestration, with FastAPI powering the backend services.

Challenges & Solutions

One of the main challenges was balancing model accuracy with inference speed. We implemented a tiered prediction system where quick ensemble models handle real-time requests, while more sophisticated transformer models run for detailed analysis during off-peak hours.