Warren Labs
Decision Infrastructure Research
Every important decision deserves better infrastructure
Decision infrastructure transforms exploration into qualified execution through evidence, validation, and continuous learning.
That's what we build.
Evaluation surface
Decision quality trace
Decision quality
The economics of intelligence
AI made ideas abundant. Judgment became scarce.
Every technological breakthrough shifts what becomes valuable.
The internet reduced the cost of information.
Cloud computing reduced the cost of computation.
AI is reducing the cost of generating ideas.
The challenge is no longer producing more possibilities.
The challenge is determining which deserve trust, action, and capital.
That qualification layer — where exploration becomes evidence and evidence becomes execution — is where Warren Labs builds.
What we build
The invisible layer behind better decisions
Decision infrastructure is not a single model or algorithm. It is a collection of systems that transform exploration into qualified execution — through evidence, validation, allocation intelligence, and continuous learning.
Qualification Systems
Systems that determine whether an idea has earned the confidence required for real-world execution.
Simulation Infrastructure
Controlled environments where decisions prove their behavior before capital exposure.
Allocation Intelligence
Decision systems that prioritize qualified opportunities using evidence, context, and continuously improving models.
Learning Systems
Feedback infrastructure that transforms every outcome into better future decisions.
Decision Infrastructure
How ideas earn execution
Every important decision begins as a possibility. Before it earns trust, it must first earn evidence. This lifecycle transforms exploration into qualified execution through validation, simulation, qualification, and continuous learning.
Generate
Explore new possibilities from context and evidence.
Validate
Measure evidence against objective criteria.
Simulate
Observe behavior in controlled environments.
Qualify
Earn the right to real-world execution.
Allocate
Prioritize opportunity with intelligence.
Execute
Deploy with precision and accountability.
Learn
Improve every future decision.
Seven stages from possibility to execution — with every outcome improving future decisions.
First Implementation
Orqis
AI-native decision infrastructure for automated capital allocation
Orqis is the first implementation of the decision infrastructure described above — applied to capital allocation, where the cost of unqualified execution is immediate and measurable.
Generate
Candidates shaped by market context, environmental awareness, and patterns learned from prior outcomes.
BTC Momentum Breakout
v1 · 4h · long-only
BTCUSDT·momentumbreakouttrendStop Loss
3.5%
Take Profit
8.0%
Leverage
2×
Qualify
Evidence scoring, simulation, and proof gates that determine whether an idea has earned live eligibility.
Validation Complete
IS / OOS split · 180 candles
Strong candidate — all thresholds met
Return
+12.4%
Sharpe
1.87
Max DD
−6.2%
Win Rate
58%
Score
72
/100
Allocate
Intelligence that ranks qualified opportunities by environmental fit, lifecycle health, and portfolio value.
Paper Trading Active
Equity
$11,240
ROI
+12.4%
Trades
23
Win Rate
61%
BTCUSDTLONGExecute
Guarded deployment with isolated execution, continuous monitoring, and access controls.
Deploy to Live
DOT Trend Momentum · 4H
ROI
+5.6%
Trades
8
Win Rate
88%
Duration
12d
Real capital · kill switch enabled
WARREN Labs' first product
Capital Governance
Capital should earn permission.
Orqis governs when, where, and how much capital a strategy is allowed to control — continuously evaluating evidence, market regime, portfolio conditions, and user-defined constraints. Governed automation, not opaque autonomy.
Dynamic Leverage
Current regime: Trending Up · Evidence: Moderate
User-enabled · bounded by system limits · adapts per regime
Dynamic Leverage
Exposure scales with evidence.
When enabled, Orqis adjusts live entry leverage according to the strength of a strategy’s demonstrated performance in the current market regime. Stronger evidence can support greater exposure, while weaker evidence keeps capital more constrained.
Leverage adapts within user-enabled settings and bounded system limits.
Permission can expand, narrow, pause, or be revoked as evidence changes.
Execution Environments
One decision system.
Multiple eligible execution environments.
Orqis separates decision intelligence from execution infrastructure. Each deployment environment retains its own eligibility, contract structure, controls, and evidence.
Crypto-native execution
Current live execution environment for eligible accounts
U.S.-regulated derivatives
Execution adapter validated end-to-end
Venue-specific eligibility, controls, and evidence. Intelligence and qualification sit above the execution layer.
Intelligence
Intelligence compounds through outcomes
Every validation, simulation, qualification, and deployment cycle produces evidence. Orqis captures those signals to improve future strategy generation, allocation decisions, and lifecycle management.
Persistent fingerprints that classify how strategies behave across family, timeframe, exits, risk, and regime assumptions.
Advisory scoring that ranks qualified strategies by regime fit, lifecycle health, behavioral consistency, diversity, and current market context.
Time-series signals showing whether a strategy’s market compatibility is stable, improving, or deteriorating.
A deterministic framework for connecting generation decisions to eventual outcomes so future candidates improve without black-box execution logic.
Principles
Operating Principles
Qualification before capital
Strategies do not move directly from generation into deployment. Capital follows evidence.
Execution stays deterministic
AI assists research, evaluation, and learning. Live capital execution follows explicit rules, permissions, and risk constraints.
Learning compounds
Outcomes improve future generation, qualification, and allocation decisions over time.
Systems over signals
We build persistent intelligence layers rather than isolated predictions.
AI-native research, deterministic execution
AI and machine learning compound across research, evaluation, and learning systems. Live capital execution remains rule-based and governed.
Active Research Threads
Qualification Systems
Evidence thresholds for deployable execution.
Active Research
Allocation Intelligence
Prioritizing qualified opportunities under resource constraints.
Active Research
Behavioral Signatures
Characterizing persistent behavioral traits across decision families.
Active Research
Regime Intelligence
Environmental conditions and their effect on decision quality.
Active Research
Outcome Attribution
Decomposing outcomes into contributing factors.
Active Research
Decision Lifecycle
Structured progression from possibility to execution.
Foundational
Learning Systems
Feedback infrastructure that compounds decision quality.
Active Research
Orqis Access
Orqis Pricing
Warren Labs' decision infrastructure for capital allocation. You only pay performance fees when strategies profit.
Pro
Validation and live deployment for independent traders
- 50 concurrent paper trading bots
- 5 live strategies on Hyperliquid
- 500 backtests + 50 optimizations/mo
- Dedicated non-custodial trading wallet
- 15% performance fee on profits only
Quant
Full access including Orqis qualified strategy deployment
- 100 concurrent paper trading bots
- 5 live strategies on Hyperliquid
- Access to Orqis qualified strategies
- 1,000 backtests + 100 optimizations/mo
- 10% performance fee on profits only
Institutional
Multi-strategy coordination and managed deployment
- Custom capacity and allocation limits
- Portfolio and exposure intelligence
- Deployment policy controls
- Managed allocation infrastructure
- Dedicated support and onboarding
Ready to start?
Access is currently admission-based during private beta.
Compare all plans and features