How We Built a Copy Trading Platform with Real-Time Signals and Auto-Following

About the Project

We developed a copy trading platform with real-time signals and auto-following for one of our key fintech clients. The platform was built on a technology stack including PHP 8.x, Node.js, React, TON SDK, Solana Web3.js, PostgreSQL, Redis, Docker, WebSocket, and GitLab CI/CD. The project was completed within 6 months with a team of 5 developers.

The client was a major financial company with existing experience in investment and trading. They were looking for a way to expand their services and offer their clients a wider range of investment tools. Our task was to create a platform that would allow clients to receive real signals and automatically follow them.

One of the main challenges was ensuring high speed and reliability of the platform, as trading requires quick decision-making. We used Docker and Kubernetes for containerization and orchestration, allowing us to scale the platform and ensure high availability.

Author: Mint Scripts Studio Team — 10+ years in Web3 and Fintech development. mintscripts.net | @mintscripts_studio

Client's Task

The client needed a platform that would allow their clients to receive real signals and automatically follow them. Additionally, the client wanted the platform to integrate with their existing infrastructure and allow them to manage all aspects of trading.

One of the main tasks was to ensure high signal accuracy and minimize loss risks. To achieve this, we used machine learning algorithms and neural networks to analyze market data and predict future trends.

The client also wanted the platform to be user-friendly and easy to use, even for novice traders. We developed a user interface that was intuitive and allowed clients to easily manage their accounts and follow signals.

Technical Challenges

One of the main technical challenges was ensuring high speed and reliability of the platform. We used WebSocket for real-time updates and Node.js to handle high loads.

Another technical challenge was ensuring signal accuracy. We used machine learning algorithms and neural networks to analyze market data and predict future trends.

We also faced the challenge of integrating the platform with the client's existing infrastructure. We used APIs and microservice architecture to ensure seamless integration and scalability.

• Technologies: PHP 8.x, Node.js, React, TON SDK, Solana Web3.js
• Database: PostgreSQL
• Caching: Redis
• Containerization: Docker
• Orchestration: Kubernetes

Solution Architecture

The platform architecture was built on a microservice basis, allowing us to scale and update individual components independently.

We used APIs to facilitate communication between components and microservices. This allowed us to ensure high flexibility and scalability of the platform.

The platform was divided into several components, including the signal module, auto-following module, and account management module. Each component was designed to provide a high level of isolation and scalability.

What the Client Received

The client received a functional copy trading platform with real signals and auto-following. The platform was integrated with their existing infrastructure and allowed them to manage all aspects of trading.

The client also achieved high signal accuracy and minimized loss risks. The platform was user-friendly and easy to use, even for novice traders.

The project was completed within 6 months with a team of 5 developers. We used Agile methodology to ensure high flexibility and scalability.

Launch a Similar Project

If you want to launch a similar project, we offer our copy trading platform development services. We have experience in fintech and can help you create a functional and scalable platform.

We also offer platform integration services with your existing infrastructure and ensure a high level of security and scalability.

For more information, please visit our website: mintscripts.net/services.html

Frequently Asked Questions

What is the main task of a copy trading platform?

The main task of a copy trading platform is to provide clients with the ability to receive real signals and automatically follow them.

What is the role of machine learning algorithms in a copy trading platform?

Machine learning algorithms are used to analyze market data and predict future trends, ensuring high signal accuracy.

What is the main technical challenge of a copy trading platform?

One of the main technical challenges is ensuring high speed and reliability of the platform, which requires technologies such as WebSocket and Node.js.