Free and paid service
NoahAI Client
Validated Windows financial OS v3.9.1.48 for crypto, stocks, and ETFs, with analysis, PAPER, permissioned execution, and records.
Learn moreNoahAI Labs•Technology
AI that connects context to validation, safe action, and continuous learning
NoahAI Labs develops an operable AI foundation that understands human problems with real-world data, verifies evidence and limits, acts only within defined permissions and policy, and turns outcomes into learning assets. Finance is the first deeply validated application; the same foundation extends to products, partner solutions, and industry programs.
For detail, see the system architecture overview: input, judgment, risk, execution, logging, and feedback layers.
CURRENT SERVICES
NoahAI is validated and in active service
NoahAI Client and Strategy Studio are available now. Strategy Hub is running as a free public test, while personal-finance capabilities are being released progressively inside the client.
Available now
Strategy Studio
Turns conversations, documents, Pine, and TradingView ideas into evidence-linked strategies for PAPER validation and operation.
Learn moreFree public test
Strategy Hub
Submit, discover, and download strategies, then revalidate them in your own environment. Paid marketplace functions remain a separate phase.
Learn moreProgressive service
Personal finance
Cash flow, goals, security alerts, tax calculation, and product-comparison capabilities are being released progressively in the client.
Learn moreAvailability varies by institution, account, and operating mode. Product comparisons are informational simulations and do not replace enrollment or execution by a financial institution.
NoahAI financial wealth OS
Not a trading tool — an OS for personal finance
NoahAI is developing a financial wealth OS that records account-level judgments, blocks, and fills to support user choice. Personal records already support later review; anonymous multi-user collective learning remains a roadmap pending consent, anonymization, revocation, and operational validation.
Self-learning judgment
AI improves the next judgment by logging and reviewing regimes and outcomes. Execution continues only within user choice and permissions.
Personal learning and collective-learning roadmap
Account-level trading and asset context are recorded now. Anonymous multi-user learning is planned only after consent, anonymization, revocation, and operational validation.
Choice support
Organize information and compare options so users do not carry judgment alone.
Multi-asset, multi-institution
Connect goals, assets, risk, everyday finance, and institutions—beyond a single investment strategy.
Judgment improves as real operation accumulates
The autonomy analogy refers to validating later judgment with operating records. NoahAI currently records account-level regimes, evidence, blocks, and fills; anonymous collective learning is not yet an operating feature. Returns are not guaranteed.
Strategy Studio (formerly AI Custom) is a core product inside this OS that structures and validates user knowledge. It is not NoahAI itself.
Operable
Real-world stack
Safety
Guardrails, halt conditions, conservative decisions
Logging / replay
Full logs, reports, reproducibility
Verification
Multi-model comparison, replay, evaluation
Feedback
Account-level record learning · anonymous collective learning is a roadmap
Multi-asset
Securities, real estate, and more
Three layers of decision infrastructure
For institutions and technical diligence, the core question is how judgments are produced, separated, logged, and replayed—not a single headline return. These three layers connect inside one stack.
1 · Decision
Decision layer
Interprets market and account state; produces policy, risk, and rationale. Designed per asset class.
System architecture →2 · Execution bridge
Execution bridge
Exchange and broker API integration. Keeps judgment and fund execution paths separable and controlled.
AI loop →3 · Audit · Replay
Audit & replay
Inputs, conditions, and outcomes are logged; conditions can be replayed and reviewed.
Technical proof →·XAI →Current technology foundation
Platform foundation
NoahAI composes financial intelligence, assets, everyday finance, and AI Custom as one operating experience on a Web UI, an independent execution engine, and a permission-separated connection layer.
Core technical composition
- • Shared judgment structure, exchange/broker execution layer, and Gateway permission · audit contracts
- • Independent operating structure that separates the screen from the execution engine
- • AI Custom is one path inside the OS: source → constrained IR/XAI → approval/PAPER/delete
- • Versioned audit records that connect judgment rationale through execution results
Change history is in the release notes, AI Custom structure in the in-depth analysis, and the overall baseline in the technical whitepaper.
Exchange support
7 registered exchange paths; order targets and readiness are specified separately
• Binance (standalone), Bybit, OKX, Bitget
• Upbit, Bithumb (LIVE-supported), Coinone (PAPER-supported; account E2E pending)
• Korean broker APIs: Kiwoom OpenAPI+, Shinhan REST, Mirae Asset REST, Korea Investment KIS REST — adapter integration regression tests completed
• Visible/learning sources are separate from live-order targets; an empty order-target list blocks new orders (0 new orders)
• The point is not registering many venues, but unifying each institution's order spec, precision, fill status, and fee structure into a shared execution layer.
HOLD and the shared execution layer
NoahAI's core action is not only buy/sell. HOLD is an active judgment that not trading is better when conditions are unmet, and that judgment is produced in a shared policy layer separate from venue-specific execution differences.
HOLD-first
Not trading is still a decision
NoahAI looks at market state, expected value, volatility, RR, and recent results together, then chooses HOLD when the bar is not met. Overall trade volume is therefore the result of valid trades that passed guardrails during parallel analysis across many accounts and markets—not indiscriminate entry.
Execution bridge
Multi-exchange and multi-broker integration
Auth methods, symbols, minimum order size, fill responses, and fee structures differ by venue. NoahAI standardizes them with adapters and a shared schema so the same judgment and risk policy can apply across institutions.
NoahAI financial AI operating structure
NoahAI is not a single execution feature. It aims to be financial AI operating infrastructure that connects financial intelligence, execution adapters, audit/safety layers, and strategy generation.
Financial intelligence
Connects market regime, account state, risk budget, portfolio, and everyday-finance data so they can be interpreted on one screen.
Exchange and broker execution adapters
Standardizes differences in order spec, precision, fill status, and fee structure into a shared execution layer.
Auditability and safety policy
Connects judgment rationale, execution requests, result logs, and halt conditions so operators can review afterward and reproduce outcomes.
AI Custom strategy management
Turns natural language, Pine, documents, images, and video sources into constrained IR and explainable strategy versions, then manages approval, PAPER, delete, and export. It is a killer capability inside the OS, not NoahAI as a whole.
Financial vertical AI operating stack
We build a financial AI stack where judgment, risk, logging, and verification work in production.
Input Layer
Real-time interpretation
We interpret market data, account/position state, and user goals together.
Decision Layer
Safety controls
Guardrails, halt conditions, and conservative decisions control risk.
Risk Layer
Risk / guardrails
Safety rules and controls limit excessive risk.
Execution Layer
Decision Support & Execution
Analyze user situation and goals to help make sound decisions. Voice consultation, scenario analysis, and reasoning explanation enable confident decision-making. Execution only proceeds with user confirmation or within pre-set ranges.
Logging Layer
Logging / replay
Full process is logged and reported for reproducibility.
Feedback Layer
Feedback / improvement
Learning at anonymized pattern level detects risk signals faster.
Guardrails
In finance, controllability matters more than speed. NoahAI designs with these principles as default.
Guardrails
Safety rules (max risk, halt conditions, etc.) are applied first.
Transparency
Judgment rationale and outcomes are logged in verifiable form.
Verification
Multi-model verification and comparison reduce bias.
Logging / replay
Every judgment and outcome is logged and reported; we look back and feed results into the next policy.
Logging
- • Judgment rationale and execution results are logged
- • Standardized format for replay
- • Learnable, auditable, traceable structure
Replay
- • Reports for replay to improve next decisions
- • Review success/failure patterns and improve
- • Verifiable in reproducible form
Verification
We provide evaluation, leaderboard, and replay systems that compare and verify models/strategies under the same conditions.
Multi-model comparison
Compare multiple models with same prompt and data
Operating metrics
Operating metrics including guardrails (stability, consistency, resilience)
Replay
Reproducible test scenarios
Extension structure
NoahAI Labs technology extends on the same judgment–logging–verification structure; it is not limited to a single asset or function.
Multi-asset
We aim to extend from initial operating experience to securities/ETF, real estate analysis, and more.
Everyday finance + voice
For users who find mobile/PC difficult, we support understanding via voice and extend to repetitive tasks (transfers, checks) and fraud/phishing risk response.
Long-term extension
NoahAI aims to provide an explainable financial assistant experience beyond smartphone/web—via voice (STT/TTS) and across devices. Our financial AI assistant technology is designed with future physical agents (robots) in mind. External integration expands step by step within clear regulation, security, and responsibility.
This describes technical extension possibility; we do not currently offer commercial robot-integrated services.
Technical documentation
This page is based on the technology we currently operate. New features are verified and released in stages.
System architecture
Core, Engine, Analyzer, Storage and extension design →
AI optimization loop
Record → Review → Policy → Risk → Feedback → XAI →
XAI (explainable AI)
Decision rationale, traceable logs, reports →
Data structure
Schema and storage for judgment/result/context →
Technical proof
Operating pipeline and log examples →
Whitepaper
Architecture, loop, safety, verification, data, roadmap →
KPI Detail & Verification Hub
AlphaArena & NoahAI user KPI metrics, formulas, and time-series trends →
NoahAI v3.9.1.48 · Strategy Studio
How Strategy Studio connects to the financial AI stack
A constrained compile-and-operate layer that turns source knowledge into explainable strategy versions for the decision, risk, execution, and audit layers.
Source → IR
Grounded nodes with supported, clarification-needed, and unsupported fail-closed capability
Validation ledger
Replay, OOS, PAPER, and fill evidence separated by version, regime, venue, and currency
Guarded execution
Permission-bound execution after regime, account, order, and venue-adapter checks
Audit · Passport
Trace decisions, HOLD, blocks, orders, fills, PnL, and version changes
Next steps
Explore our production financial AI stack and how it shows up in services.