Agents propose.
Systems execute.
Give AI agents access through the same services your team uses. Keep accounting, order state, and risk enforcement in the deterministic core.
BUILT FOR SYSTEMATIC TEAMS
Good research.
Disciplined
execution.
The operating layer for quantitative trading teams. Bring research, AI agents, and paper execution into one governed workflow.
Currently in private beta · Research & paper trading
THE ARDEN OPERATING LAYERFIG. 01
Research team AI agents
arden.
DETERMINISTIC CORE✓Shared risk controlsGATE
↳
Paper executionEvery decision leaves a record.
↗ONE CONNECTED FOUNDATION
Versioned researchDeterministic backtestsShared risk controlsInspectable decisions
01 / THE WORKFLOW
From a promising idea
to a process you can inspect.
Less stitching together notebooks, brokers, and logs. More clarity at every step.
START WITH CONTEXTA strategy is more
A strategy is more
than its latest file.
Keep the strategy version, parameters, and data behind each experiment together. Give researchers and agents a common starting point.
- Versioned strategy definitions
- Archived research inputs
- One workflow across UI, Python, and MCP
strategy.manifest ILLUSTRATIVE
strategymomentum_research
versionv3 PRESERVED
parameterslookback · universe · sizing
inputsarchived with the run
interfaceUI / Python / MCP
MAKE RESULTS REPRODUCIBLEKnow what went
Know what went
into every result.
Run strategies against explicit data and execution assumptions. Preserve the inputs and configuration so a result can be inspected and replayed.
- Signals at close; simulated fills at next open
- Explicit fees and slippage assumptions
- Saved data, engine, and configuration fingerprints
run.manifest ILLUSTRATIVE
strategymomentum_research / v3
signalssession close
fillsnext session open
data sourceexplicitly recorded
run recordimmutable SAVED
PUT POLICY IN THE PATHOne set of controls.
One set of controls.
Every order intent.
Researchers, agents, and replay all go through the same execution and risk services. Inspect the policy and reason behind each decision.
- Position, exposure, and order limits
- Workspace pause and kill controls
- Versioned policies and decision snapshots
risk.decision ILLUSTRATIVE
Order intent
SHARED RISK SERVICEEvaluate against current policyAllow or reject, with a recorded reason.
CLOSE THE LOOPPractice execution.
Practice execution.
Keep the evidence.
Move from research into simulated replay or an Alpaca paper account. Follow order state, positions, and the decision trail in one workspace.
- Paper execution with broker reconciliation
- Persistent worker and order recovery
- Downloadable audit evidence
execution.record ILLUSTRATIVE
Intent queuedStrategy version attached
Risk preflightCurrent policy evaluated
Paper brokerSubmission and reconciliation
Audit recordConfirmed state preserved
Interactive product overview. Illustrations describe the workflow; they are not live account data.
02 / THE PRINCIPLE
Intelligence can change.
The controls shouldn’t.
Use AI where it helps. Keep execution deterministic, governed, and observable.
Agents propose.
Keep the context.
Not just the result.
Connect each run to its strategy version, data, and configuration. Understand how an experiment happened and what changed between versions.
Research to execution.
One decision trail.
Carry your work into paper trading with shared controls and inspectable records, from the original intent to the confirmed broker state.
BUILT FOR THE NEXT GENERATION OF QUANT TEAMS
Spend more time on the idea.
Less on the infrastructure.
We’re building Arden with quantitative researchers and systematic trading teams.
Start a conversationTell us about your research workflow and what you want to build.