The Story

StratifyPro sought to revolutionize trading strategy creation by enabling non-technical users to develop and backtest algorithmic trading strategies without coding. By leveraging AI and natural language processing, the platform allows users to input trading goals and receive back-testable models optimized for various stock indicators. This innovation bridges the gap between complex trading concepts and everyday traders.

The client is a leading strategy management platform combining AI-powered tools, expert coaching, and proven methodologies to help businesses execute strategies faster, align teams, and achieve remarkable growth.

Amit Jangid

Founder & CTO

Challenges

• > Users lacked coding expertise to create executable trading models.

• > Stock market jargon required tailored AI training for precise query handling.

• > Ensuring real-time backtesting and execution under high user demand.

• > Providing instant, accurate responses to platform-related queries.

• > Deploying scalable, low-latency backend systems.

The Solution

StratifyPro was developed as an AI-powered trading assistant built on a Flask framework. Using GPT-4o for strategy generation, RASA NLU for stock-specific queries, and RAG with a vector database for instant knowledge retrieval, the platform enabled no-code strategy creation. Real-time backtesting, a library of proven strategies, and Amazon EC2 deployment ensured scalability and low latency.

The Outcome

StratifyPro transformed trading by making it accessible to non-technical users. The platform facilitated no-code strategy generation, instant backtesting, and seamless broker integration. With scalable deployment and AI-powered support, it enhanced user experience and efficiency, empowering traders to create and execute strategies effortlessly.