We don’t predict the market — we adapt to it.

NovoXpert is a financial AI startup focused on building adaptive intelligence systems for real-world decision-making in financial markets. Our mission is to create a new generation of intelligent platforms that transform complex financial data into living, risk-aware, and context-driven decisions.

NovoXpert is currently developing two main projects — both founded on adaptive, multilayered AI architectures:

A multimodal, risk-aware, and reflective AI system for financial reasoning.

AlphaFusionNet forms the analytical and technical backbone of the NovoXpert ecosystem. It is a deep, multi-stage learning architecture that fuses price data, news sentiment, fundamentals, and network relationships to produce a unified understanding of market dynamics.

AlphaFusionNet is built on three guiding principles:

1. Fusion of diverse signals: Integrating market, news, and network information into a coherent analytical view.
2. Dynamic risk perception: Continuously adjusting to changing volatility and market regimes.
3. Feedback-driven improvement: Using each decision’s outcome as input for the next learning phase, enhancing precision over time.

Transforming the AlphaFusion architecture into autonomous decision-making agents.

MarketPilot is the next-generation evolution of AlphaFusionNet — a system where AlphaFusion’s analytical models and financial features are extended with agentic reasoning and reinforcement learning feedback. Here, the system not only analyzes the market but also acts as an intelligent agent that decides, evaluates outcomes, and learns continuously.

MarketPilot evolves along three key dimensions:

1. Scenario and language reasoning: Leveraging LLMs to interpret macroeconomic narratives and contextual sentiment.
2. Adaptive market behavior: Dynamically shifting strategies across bull, bear, and crisis phases.
3. Self-regulation through feedback: Every action becomes a data point for continuous learning and improvement.

• Top-Allocations: Highest-ranked portfolio positions based on risk and return
• Entry/Exit Signals: Suggested trade points with confidence levels
• Portfolio Metrics: CVaR, Sharpe, Drawdown, and performance analytics
• Explainability: Visualized expert contribution and reasoning transparency (Explainable MoE)

While AlphaFusionNet is designed around structured models and engineered features, MarketPilot adds an agentic layer of reasoning and reinforcement learning, allowing the system to adapt its behavior through real-world feedback. This version represents our operational prototype, marking the startup’s transition from research architecture to market-ready intelligent agents.

Website: www.novoxpert.com
Email: [email protected]
Phone: +90 531 656 2474
Locations: Istanbul — Operating Globally