AI-POWERED FINANCIAL TECHNOLOGY

Intelligence that
transforms
institutional finance.

Xinghan Yunhang's proprietary Cloud–Data–Intelligence platform unifies big data processing, AI model training & inference, low-latency execution, and compliance risk control — from research to audit, end to end.

Explore Our Platform → About Xinghan Yunhang
99.9%
Core system availability target
ms
Millisecond-level circuit stability
B2B
Exclusively for institutional clients
3×
SaaS · Private cloud · On-premise
// PLATFORM STATUSLIVE
AI Inference Engine● ONLINE
Risk Control Models● ACTIVE
Data Pipelines● RUNNING
Compliance Audit● PASSING
Anomaly Alerts0 DETECTED
Model confidence · Real-time
⚡
AI Trading System
Low-latency research and execution framework with AI-assisted decision support and built-in trading governance.
🛡
Risk Control System
Real-time AI anomaly detection, scenario stress testing, MRM, and compliance monitoring with full attribution reporting.
📊
Data Analytics System
Unified big data pipelines, AI model training, and visualization — from raw data to actionable investment intelligence.
🔒
Compliance by Design
Cross-border data governance, model explainability, and regulatory compliance baked into every layer of the platform.
// ABOUT THE COMPANY

Built for the demands of institutional finance.

Shanghai Xinghan Yunhang Technology Co., Ltd. is an AI and big-data-driven financial technology company. We provide institutional clients with an integrated suite of AI-assisted trading, risk control, and data analytics systems designed for multi-market, multi-asset environments.

Our self-developed "Cloud–Data–Intelligence" platform is the operating backbone for research, trading, risk management, and compliance auditing — all in a single coherent architecture, with SaaS, private cloud, and on-premise deployment options.

Learn More → See Solutions
5+
Institutional clients — 12-month target
30+
Cumulative clients — 36-month target
99.9%
Core system availability SLA
ISO
9001 & 27001 certification in progress
// PRODUCTS & SERVICES

Three core systems.
One unified AI platform.

From trading decisions to risk oversight, from raw data to compliance audit — Xinghan Yunhang delivers end-to-end intelligent infrastructure purpose-built for financial institutions across every asset class.

⚡
AI Trading System
A unified low-latency research and execution framework with AI-assisted alpha research and decision support. Every component — from data ingestion to order routing — is orchestrated within a single coherent architecture, eliminating the operational friction of fragmented toolchains.
  • Low-latency research and execution framework for systematic strategies
  • AI-assisted alpha generation, backtesting, and signal validation
  • Real-time decision support with model confidence scoring
  • Multi-venue order routing with smart execution algorithms
  • Trading governance module for pre-trade compliance enforcement
  • Full audit trail and post-trade reporting
Low-LatencyAI ResearchBacktestingTrade GovernanceMIS Reporting
🛡
Risk Control System
An institutional-grade risk platform that combines AI-driven anomaly detection with rigorous quantitative risk models. Designed for multi-asset portfolios with complex cross-market exposures, it delivers real-time risk intelligence from pre-trade through post-settlement.
  • AI-powered real-time anomaly detection and early-warning alerts
  • Scenario generation and stress testing across historical and hypothetical shocks
  • Compliance rule modeling and automated orchestration
  • Trade compliance monitoring with real-time breach detection
  • Model Risk Management (MRM) — model cards, validation, and lifecycle tracking
  • Intraday and post-trade attribution, P&L decomposition, and regulatory reporting
  • Configurable safety and compliance boundary engine
AI Anomaly DetectionStress TestingMRMCompliance MonitorAttribution
📊
Data Analytics System
A production-grade big data platform that serves as the shared data foundation for all AI workloads. It normalizes heterogeneous market data, supports large-scale model training, and delivers insights through a unified visualization layer accessible to both quant researchers and business stakeholders.
  • Ingestion and normalization of multi-asset, multi-venue market data
  • Feature engineering pipelines for machine learning and statistical models
  • Distributed AI model training with GPU support
  • Online model serving with low-latency inference APIs
  • Interactive dashboards and customizable analytics views
  • Data lineage tracking and version control for reproducibility
Big DataAI TrainingGPU ComputeVisualizationData Lineage
// CORE TECHNOLOGY

Three technology pillars.
Enterprise-grade reliability.

A proprietary architecture engineered for the intersection of extreme performance and strict regulatory compliance — cloud-native infrastructure, millisecond resilience, and governed AI at every layer.

01 / CLOUD-NATIVE & DISTRIBUTED
Elastic, Always-On Architecture
Kubernetes and Service Mesh orchestration with elastic auto-scaling and multi-active high availability. Task scheduling, workflow orchestration, and full-stack observability — logs, distributed tracing, and real-time metrics — enable operational teams to monitor every component with precision. The architecture is designed for zero-downtime deployments and rapid incident response, meeting the continuous availability demands of financial market operations.
02 / LOW LATENCY & RESILIENCE
Millisecond Circuit Stability
Publish-subscribe messaging, in-memory cache with replay capability, and configurable self-healing degradation strategies collectively ensure that trading circuits remain stable even under extreme market conditions. The system is designed to fail gracefully: when individual components degrade, automated fallback mechanisms prevent cascading failures, preserving order flow and risk data integrity throughout.
03 / DATA & MODEL GOVERNANCE
Compliance-Driven Intelligence
Data classification by sensitivity level and domain, with a minimization-by-design philosophy. Cross-border and cross-jurisdiction data flow compliance assessment workflows are embedded in the platform, supporting both domestic PRC requirements and international client regulatory demands. Model cards, standardized benchmarking, and explainability frameworks ensure every AI model deployed in production is auditable, interpretable, and aligned with regulatory expectations.
// DEPLOYMENT

Flexible deployment.
Three modes, one platform.

Whether you need a rapid SaaS onboarding, a fully isolated private cloud, or a completely on-premise installation with data never leaving your infrastructure — Xinghan Yunhang supports all three models with the same feature set and compliance posture.

☁️
SaaS
Rapid onboarding with managed infrastructure. Ideal for clients who want immediate access to the full platform without internal DevOps overhead. Hosted in compliance with applicable data residency requirements.
🏢
Private Cloud
Dedicated cloud environment — isolated compute, network, and storage — operated on behalf of the client. Combines the operational simplicity of cloud with the data control of on-premise.
🖥
On-Premise
Full local deployment within the client's own data center. Data never leaves the client's infrastructure. Optimal for institutions with strict data sovereignty requirements or existing data center investments.
// SOLUTIONS

Vertical solutions for
every institutional profile.

Exclusively B2B. Serving the full range of institutional financial clients across multi-asset environments — with deployment flexibility and cross-border compliance built in from the ground up.

Asset Management Firms
For public funds, private funds, and hedge funds, Xinghan Yunhang delivers a complete research–trading–risk–compliance loop. The platform eliminates the fragmentation that typically afflicts institutional investment operations — integrating factor research, portfolio construction, execution, real-time risk monitoring, and regulatory reporting into a single governed environment.

AI-assisted alpha generation and strategy backtesting are backed by the full power of the data analytics engine, while the risk control system provides real-time portfolio-level risk visibility and automated compliance enforcement — enabling fund managers to focus on investment decisions rather than operational plumbing.
  • AI factor research, signal generation, and strategy backtesting platform
  • Multi-strategy live trading execution and portfolio management
  • Real-time portfolio risk monitoring and limit management
  • Automated compliance boundary monitoring and pre-trade checks
  • Model Risk Management (MRM) framework for investment models
  • Intraday and end-of-day attribution analysis and performance reporting
  • Regulatory reporting and audit trail generation
// KEY CAPABILITIES
Supported asset classesEquities, FI, Futures, FX, Options
AI model typesFactor, time-series, multi-modal
Risk metricsVaR, CVaR, stress, attribution
DeploymentSaaS / Private / On-premise
CompliancePRC + client jurisdiction
Prime Brokers &
Clearing Houses
Prime brokers and clearing institutions face the challenge of managing risk across hundreds of client accounts simultaneously while maintaining real-time visibility into aggregate exposures. Xinghan Yunhang's platform provides a purpose-built infrastructure layer that combines multi-client account segregation, real-time margin monitoring, and AI-powered anomaly detection into a unified operational environment.

Automated clearing and settlement workflows, combined with regulatory reporting templates tailored to specific market requirements, dramatically reduce the manual overhead of compliance operations while improving the accuracy and timeliness of reporting.
  • Multi-client account segregation with real-time risk isolation
  • Real-time margin monitoring and automated margin call workflows
  • AI-powered anomalous trading behavior detection and alerting
  • Automated clearing and settlement workflow management
  • Post-trade attribution and client-level P&L reporting
  • Regulatory reporting tailored to exchange and clearing house requirements
  • Security and compliance boundary enforcement across all client accounts
// KEY CAPABILITIES
Account managementMulti-client, real-time segregated
Margin monitoringReal-time, automated alerts
Anomaly detectionAI-driven, sub-second latency
ReportingAutomated, regulatory-template
DeploymentPrivate cloud / On-premise
Market Makers &
Liquidity Providers
Market making and liquidity provision demand the highest levels of system performance and risk precision. Xinghan Yunhang's platform is engineered for the specific operational profile of market-making firms — millisecond-level quote strategy support, real-time inventory and exposure monitoring, and sophisticated risk controls that adapt dynamically to market conditions.

The platform's AI anomaly detection layer provides early warning of unusual market microstructure patterns, while the stress testing module helps quantify tail risk exposures in illiquid or stressed scenarios. Compliance monitoring ensures all quoting and execution activity remains within defined regulatory boundaries across multiple markets simultaneously.
  • Millisecond-level low-latency execution and quote management framework
  • Real-time inventory monitoring and automated exposure rebalancing
  • AI-powered market microstructure anomaly detection
  • Multi-market compliance monitoring and breach alerting
  • Scenario-based stress testing for liquidity risk quantification
  • Liquidity risk model development, validation, and management
  • Cross-venue position aggregation and net exposure reporting
// KEY CAPABILITIES
Execution latency targetMillisecond-level
Inventory monitoringReal-time, multi-venue
Markets supportedEquities, Futures, FX, Options
Risk modelsLiquidity VaR, stress scenarios
DeploymentOn-premise preferred
Multi-Asset
Quant Firms
Multi-asset quantitative firms operate at the intersection of data science, financial engineering, and technology — requiring infrastructure that can keep pace with both research innovation and production demands. Xinghan Yunhang's Cloud–Data–Intelligence platform is purpose-built for this profile: a unified data and model layer that spans equities, futures, options, FX, and fixed income, with seamless promotion of research-stage models into live trading.

The platform's data management layer centralizes normalization and feature engineering across all asset classes, while the AI training environment provides GPU-accelerated model development with built-in versioning, validation, and governance — enabling quant teams to iterate rapidly without sacrificing the rigor required for production deployment.
  • Unified multi-asset data pipelines — equities, futures, options, FX, fixed income
  • Centralized feature engineering and data catalog management
  • GPU-accelerated AI model training with experiment tracking
  • Seamless research-to-production model promotion workflow
  • Cross-asset risk aggregation and portfolio-level analytics
  • Data classification, localization, and cross-border compliance
  • SaaS, private cloud, or on-premise deployment with identical feature set
// KEY CAPABILITIES
Asset classesEquities, Futures, FX, FI, Options
Model trainingGPU-accelerated, versioned
Research-to-prodIntegrated workflow
Data governanceClassification + cross-border
DeploymentSaaS / Private / On-premise

Ready to discuss your requirements?

We work exclusively with institutional clients. Our team will assess your specific infrastructure, regulatory context, and deployment preferences before proposing a solution architecture.

Contact Our Team →
// ABOUT US

About Xinghan Yunhang.

A company founded on the conviction that AI can fundamentally transform how financial institutions operate — not just augmenting existing workflows, but reimagining the entire infrastructure stack from the data layer upward.

// COMPANY OVERVIEW

The Cloud–Data–Intelligence platform.

Shanghai Xinghan Yunhang Technology Co., Ltd. is an AI and big-data-driven financial technology company. We provide institutional clients with an integrated suite of AI-assisted trading systems, risk control systems, and data analytics systems — engineered for multi-market, multi-asset environments at institutional scale.

The company's self-developed "Cloud–Data–Intelligence" integrated platform spans the complete operational chain: from raw market data ingestion and big data processing through AI model training, online inference, low-latency trade execution, and compliance risk control — all within a single coherent architecture. This end-to-end integration eliminates the translation losses and operational gaps that typically arise when institutions stitch together point solutions from multiple vendors.

Xinghan Yunhang provides technology and system services exclusively. We strictly maintain our business boundary: we do not engage in discretionary asset management, fund raising, proxy trading, or any activity requiring a financial license, and we do not offer public-facing trading channels or off-exchange brokerage services. Our mandate is to be the best-in-class technology partner for institutions that manage those activities themselves.

ISO 9001 — In Progress ISO/IEC 27001 — In Progress MLPS 2.0 Cross-border Compliance B2B Only
5+
Institutional clients — 12-month target
30+
Cumulative clients — 36-month target
99.9%
Core system availability target SLA
5
Software copyright or patent filings planned
// CORE VALUES
Institutional Trust
Financial institutions entrust us with their most sensitive data and most critical workflows. We earn that trust through transparency, rigorous compliance, and unwavering reliability.
AI Without Compromise
Every AI model we deploy in production is explainable, auditable, and governed. We believe responsible AI and high-performance AI are not in tension — they are the same thing done properly.
Technology Partner, Not Vendor
We build long-term relationships with clients, co-designing solutions to their specific infrastructure, regulatory context, and strategic objectives — not selling off-the-shelf software.
// OUR TEAM

Leadership built on
deep expertise.

A founding team combining world-class AI research, financial engineering, distributed systems engineering, and institutional compliance operations — united by a shared conviction that technology can fundamentally improve how financial markets function.

He Lianxin
He Lianxin
CEO · CHIEF SCIENTIST — AI & DATA SCIENCE
Leads the company's strategic direction and scientific research agenda. Brings deep expertise in artificial intelligence and data science applied to financial markets, overseeing the development of the Cloud–Data–Intelligence platform and the company's core AI capabilities. Responsible for translating cutting-edge research into production-grade systems that meet the reliability and compliance standards of institutional finance.
Tao Tianwen
Tao Tianwen
ALGORITHM LEAD — ML / TIME SERIES / MULTI-MODAL
Leads the design and development of the company's core algorithms across machine learning, time-series forecasting, and multi-modal AI. Responsible for the research-to-production pipeline, model validation frameworks, and the ongoing improvement of the AI Trading System's alpha generation capabilities. Brings research-grade rigor to every model that enters the production environment.
Li Wei
Li Wei
CTO — DISTRIBUTED SYSTEMS & CLOUD-NATIVE
Architects and leads the development of the company's core technology infrastructure. Expert in distributed systems, cloud-native architecture, and high-performance computing, with particular focus on the low-latency and resilience requirements of financial market applications. Oversees the engineering of Kubernetes-based orchestration, Service Mesh, and the observability stack that underpins the platform's enterprise-grade reliability.
Wan Yi
Wan Yi
OPS & COMPLIANCE LEAD — DATAOPS / PROCESS ENG. / MODEL GOVERNANCE
Leads operational excellence and compliance governance across the organization. Responsible for DataOps pipelines, process engineering, and the model governance framework — ensuring that every data asset and AI model deployed in production meets the company's standards for quality, traceability, and regulatory compliance. Oversees the progress toward ISO 9001, ISO/IEC 27001, and MLPS 2.0 certification.
// ROADMAP

Clear milestones.
Disciplined execution.

Concrete, measurable targets at each phase of growth — from platform launch and first institutional clients through to scaled operations, certification, and recognition as a leading specialized technology company.

Phase 1 · 12-Month Target
Platform Launch & First Clients
  • Complete and ship the Data–Model–Execution–Risk unified platform V1.0, with all three core systems production-ready
  • Go live with a minimum of 5 institutional financial clients across at least two client segments
  • Achieve core system availability of ≥ 99.9% across all production deployments
  • File a minimum of 5 software copyrights or patents covering core platform innovations
  • Establish initial compliance framework and begin ISO 9001 certification process
Phase 2 · 36-Month Plan
Scale, Certification & Recognition
  • Develop 2–3 replicable institutional-grade benchmark solutions that can be deployed efficiently across similar client profiles
  • Grow cumulative client base to ≥ 30 financial institutions, diversified across client segments and asset classes
  • Complete ISO/IEC 27001 information security management certification and MLPS 2.0 assessment and remediation
  • Achieve recognition as a National High-Tech Enterprise and Specialized & Innovative (专精特新) company
  • Expand cross-border compliance capabilities to support clients operating in multiple regulatory jurisdictions
// COMPLIANCE & GOVERNANCE

Compliance built in,
not bolted on.

Every layer of our platform is designed around regulatory requirements — from data residency and model explainability to business boundary enforcement and certification standards.

🔒
Business Boundary
Xinghan Yunhang provides technology and system services only. We do not engage in discretionary asset management, fund raising, proxy trading, discretionary holding, or any activity requiring a financial license. We do not offer public trading channels or off-exchange brokerage services of any kind. This clear business boundary protects both our clients and our integrity as a technology partner.
⚖️
Legal & Regulatory
Domestic operations strictly comply with PRC laws, administrative regulations, and applicable local regulatory rules. For scenarios involving cross-border data flows or cross-jurisdiction access, we establish compliance assessment and regulatory filing procedures as required, and execute all data handling in accordance with each client's applicable local regulatory requirements — including data localization, access controls, and audit trail requirements.
🏅
Certification Roadmap
Actively progressing toward ISO 9001 quality management system certification and ISO/IEC 27001 information security management certification. Implementing Multi-Level Protection Scheme (MLPS) 2.0 security assessment and remediation for all applicable system components. These certifications provide independent validation of the company's commitment to operational quality and information security standards.
🧠
Model Governance
Every AI model deployed in a production environment is subject to the company's Model Risk Management (MRM) framework — including model cards documenting intended use, known limitations, and performance benchmarks; validation against held-out data; and ongoing performance monitoring post-deployment. Explainability requirements are applied to models used in compliance-sensitive contexts, ensuring that model outputs can be fully explained to regulators and audit teams.
🌐
Data Governance
Data is classified by sensitivity level and domain, with access controls enforced at the data layer. The platform implements a minimization-by-design philosophy — processing only the data required for each specific function, with full lineage tracking enabling complete audit trails. Cross-border data handling undergoes formal compliance assessment before implementation, with documented procedures aligned to applicable regulations including PRC data security and cross-border transfer requirements.
🔐
Information Security
The platform incorporates defense-in-depth security architecture: network segmentation, encryption at rest and in transit, role-based access control, privileged access management, and comprehensive security event logging. Regular penetration testing and security assessments are conducted to validate controls. The information security program is structured around the ISO/IEC 27001 standard, with certification in progress, providing clients with independent assurance of the company's security posture.