AI-Powered Investment Marketplace for Crypto Strategies

• Project: AI-based infrastructure development to configure and manage crypto investment strategies
• Technologies: React, Tailwind, Node.js, WebSocket feeds, Koa, custom AI simulation module

The client is a digital investment startup bridging the gap between retail and institutional investors in the crypto space.

The Client’s Request

The client approached Velvetech with a clear objective: to design and develop a modular platform that could support the full lifecycle of algorithmic investment strategies, from creation and simulation to capital allocation and performance tracking. Central to the vision was a robust strategy logic engine, enhanced by AI, capable of simulating and optimizing strategies before deployment.

It was essential to support two distinct user roles: investors and strategy managers, each with their own tailored dashboards, permissions, and workflows. Investors’ priority was transparency and ease of allocation, while managers required fine-grained control over logic, inputs, and outcomes.

Real-time data analytics was also a core requirement. The platform had to provide visibility into yield performance, risk exposure, historical drawdowns, and PnL — not in delayed reports, but live, at a glance. Additionally, the system needed to handle private and public strategy access with granular permissions, including referral-based entry and invite-only vaults.

Finally, the client emphasized the importance of long-term scalability. While MVP development implied core functionality implementation, the underlying architecture had to support smooth future expansion, including tokenized capital flows, smart contract vaults, and integration with on-chain data sources.

Taking note of extensive blockchain-related experience and AI implementation, Velvetech was selected as an AI investment software development partner for this project.

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The Process

Velvetech began with a deep dive into the client’s early technical architecture, use cases, and failed MVPs. Based on our analysis, we proposed a clean-slate build that centered on modularity, user control, and real-time data visibility.

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The initial phase focused on delivering an MVP that would bring together four pillars: strategy creation, AI-assisted simulation, investment execution, and performance monitoring.

React and Tailwind were used to create a clean, responsive user interface for strategy configuration and performance monitoring. On the backend, we implemented a lightweight but powerful architecture with Node.js and WebSocket feeds for real-time updates. The AI simulation layer allowed managers to test and optimize strategy parameters before deployment.

As the platform grew, new modules were added — including investor dashboards, strategy access control, and admin tools for monitoring user activity and platform usage.

AI and Strategy Configuration

The core of the platform lies in its strategy builder: a configurable logic engine supported by AI modules. Managers can define custom strategies using if/then conditions, moving averages, market indicators, and volatility constraints. These strategies can then be simulated using historical data to validate performance under various market conditions.

The AI integration in the investment platform assists managers by suggesting optimal parameter configurations based on selected benchmarks, such as the Sharpe ratio, max drawdown, or historical returns. Users can experiment with multiple logic layers, compare outcomes, and deploy strategies once they’re satisfied with the simulations.

Each strategy is versioned, traceable, and accompanied by clear performance data, including real-time metrics, risk profiles, and capital allocation history.

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Result and Future Plans

The MVP was successfully delivered and is already an end-to-end investment platform solution, with investors already allocating capital to early strategies. Managers can deploy, update, and monitor their logic modules, while investors get full visibility into yield, risk, and transaction flow.

Initial traction showed strong adoption of AI-augmented strategies, with over a dozen logic templates launched in the first release phase. The platform has proven capable of supporting custom strategy vaults, and its infrastructure is prepared for smart contract integrations, referral systems, and future tokenization features.

Looking ahead, the platform is expected to expand to new asset classes and partner ecosystems. The modular design enables fast rollout of additional strategy types, broader investor features, and even cross-chain deployment, ensuring the solution’s flexibility.