HeloraAIWhere Artificial Intelligence Meets Alpha
HeloraAI builds institutional-grade, auditable AI systems for quantitative and derivatives trading, combining deep learning, reinforcement learning, and systematic execution.
Helora Core Engine
Deep Learning · Reinforcement Learning · Quant Modeling
- • QuantMatrix™ — automated factor generation & model training
- • ReinforceX™ — adaptive execution & position sizing
- • Risk Sentinel™ — predictive AI risk monitoring
- • Helora Cloud — GPU/FPGA hybrid infra; ~2-hour model refresh cycles
About HeloraAI
HeloraAI is a U.S. corporation focused on AI-driven quantitative and derivatives trading. We operate a closed intelligence loop that turns multi-modal data into trading signals and signals into execution with full model and log auditability.
Our platform synchronizes backtest and live environments across multiple venues, running at millisecond-level latency with integrated risk controls and versioned models designed for institutional use.
Highlights
- • Strategy clusters: trend/momentum, stat-arb, volatility, market-neutral, HFT market making
- • 120+ TB historical & multi-modal data; 1.5+ TB processed per day
- • Smart Order Router & microstructure-aware order slicing
- • Environments synchronized across major exchanges for backtest-to-live consistency
Technology & Innovation
A unified stack that fuses AI research, systematic trading, and risk engineering.
QuantMatrix™
Automated feature engineering and factor selection with multi-modal inputs: price, order book, flows, macro, on-chain metrics, news, and social sentiment.
ReinforceX™
Reinforcement-learning based execution layer using real-time PnL feedback for route optimization and dynamic position sizing.
Risk Sentinel™
Predictive VaR and drawdown forecasting, anomaly detection, and automated de-leveraging and circuit-breaker mechanisms across strategies and venues.
Trading & Performance
- • Multi-asset strategies covering derivatives, perpetuals, and cross-exchange opportunities.
- • Backtest/live parity with version-controlled models, configs, and execution logs.
- • Latency-optimized infrastructure with colocation and FPGA-based market data processing.
Extreme Market Windows
Volatility strategies are designed to preserve net value during high-volatility regimes and macro events. All results are clearly labeled as back-tested or live, with defined time windows and assumptions.
Regulatory & Corporate Information
Incorporation (Colorado, USA)
| Legal Name | HeloraAI Ltd |
| Entity Type | Colorado Corporation |
| Entity ID | 20258208700 |
Articles of Incorporation, Certificate of Good Standing, and filing certificates are available upon request.
Federal Tax (IRS)
| EIN | 41-2342269 |
| IRS Notice | CP 575 |
All federal filings use the exact legal name and EIN as shown on the IRS notice.
MSB Registration (FinCEN)
Status: Registered
Documentation listed here can be provided under NDA or via a secure data room for institutional counterparties.
Leadership & Advisory Board
Leadership Team
Ethan Ward — Chief Executive Officer
Former Head of Systematic Trading at Citadel Securities and Director of AI Financial Systems at Google AI. Over 15 years of experience in quantitative and high-frequency trading, responsible for HeloraAI's global strategy and technology integration.
Dr. Melissa Turner — Chief Technology Officer
Ph.D. in Computer Science from MIT, former Senior Research Scientist at Two Sigma. Expert in reinforcement learning and multi-modal modeling. Leads development of the Helora Core Engine and the firm's algorithm transparency framework.
Robert Chen — Chief Strategy Officer
Former Derivatives Trading Lead at Jane Street Capital, with 12 years of experience in derivatives and volatility trading. Oversees strategy research, model evaluation, and optimization of execution across venues.
Dr. Michael Hartmann — Chief Risk Officer
Former Global Risk Director at AIG, Ph.D. in Financial Engineering from Oxford University. Leads HeloraAI's AI-driven risk and compliance framework, including the design and oversight of the Risk Sentinel™ predictive monitoring system.
Advisory Board
Prof. Andrew Reinhardt — Research Director, Stanford AI Lab
Specialist in reinforcement learning and financial behavior modeling, providing strategic and academic guidance for HeloraAI's AI research.
Dr. Lisa Mason — Former Quant Lead, DeepMind
Focused on reinforcement learning and optimization algorithms, advising on the evolution of the ReinforceX™ execution engine.
John Roberts — Former Director of Digital Assets Technology, Goldman Sachs
Veteran in fintech and regulatory technology. Supports blockchain audit architecture and implementation of FinCEN/MSB-aligned processes.
Dr. Elena Kovalchuk — Former Senior Quantitative Analyst, Morgan Stanley
Expert in multi-factor regression and portfolio optimization, consulting on quantitative model validation and risk modeling.
David Kim — Former Partner, BlackRock AI Research
Experienced in AI-driven investment design and asset allocation, advising on institutional strategy and strategic partnerships.
Roadmap
HeloraAI follows a staged roadmap from initial research and architecture design to full-scale institutional deployment and global ecosystem expansion, aligned with our whitepaper.
2023 Q4
• Project inception and technical route design
• Initial data pipeline and factor library
• Early experiments with deep learning and RL models
2024 Q1–Q2
• Helora Core Engine prototype online
• ReinforceX™ execution module in internal testing
• Integration of on-chain and sentiment data
• Initial backtesting framework established
2024 Q3–Q4
• Trend, arbitrage and volatility strategy clusters formed
• Multi-modal data engine in production
• Risk Sentinel™ early version deployed for testing
• Deeper integration with GPU/FPGA compute
2025 Q1–Q2
• Small-scale live trading (grey-mode)
• Strategy lifecycle management and model audit framework
• Latency and routing optimization
• Design of institutional-grade compliance modules
2025 Q3–Q4
• U.S. incorporation completed and EIN obtained
• FinCEN MSB registration application submitted
• Limited access for pilot institutional clients
• Full strategy cluster risk coordination in place
2026 Q1–Q3
• Commercial rollout of strategy and data services
• Helora AI Terminal (Beta) launched for professionals
• Model subscription and execution optimization APIs
• Deeper integration with exchanges and brokers
2026 Q4–2027 Q2
• Regional partnerships in Singapore and Hong Kong
• Expansion to additional derivatives markets
• Long-term collaboration with European institutions
• Enhanced on-chain audit tools and KYC/AML modules
2027 Q3–Q4
• Helora Developer Framework for third-party strategies
• External developer ecosystem onboarding
• Full automation of internal audit and compliance loops
• Second-generation portfolio optimization architecture
2028+
• Distributed intelligent trading network
• Unified AI execution layer across markets and assets
• Positioning as core infrastructure for institutions
• Driving higher standards for AI financial regulation
Contact
HQ: New York • Additional Offices: Singapore • London
Vision
We believe AI will profoundly reshape global trading. HeloraAI will always stand at the forefront of the convergence of technology and finance, driving intelligent trading into a new era.