POST-LAUNCH OPERATIONS
Live Network Control Center
Observe the deployed economy, detect drift and risk, and simulate bounded policy changes before any human-approved execution.
Network health
Current Economy State
Connect a deployed token and synchronize evidence to populate live market, liquidity, treasury, utility and risk metrics.
Data integrity
Evidence & Providers
Provider health has not been tested.
Operational risk
Drift & Alerts
No live observations are available.
Controlled response
Policy Simulation Queue
1DetectEvidence-backed drift or risk signal
2SimulateBuyback, tax, treasury or governance counterfactual
3ApproveExplicit human approval and audit reference
4HandoffExport configuration; no automatic chain execution
No policy counterfactual has been simulated.
STEP 2 · GATEKEEPER
Utility & Compliance Wall
Prove that product usage creates token demand and clear the internal design-risk screen before optimization.
Demand & Sink Results
Run the gate to calculate usage demand, market purchases, burn, retention and token velocity.
Hard Stops & Warnings
The design has not been screened.
Required Changes
No remediation plan yet.
Progression decisionRun the gate before entering the Optimizer.This is an internal product-risk screen, not final legal advice.
Step 4
Validation & Calibration
Measure forecast error on evidence that was not used to fit or select the model.
Validation Decision
Run Step 3, then validate its timestamped forecast.
Error & Skill
No error metrics.
Regime Stability
No regime analysis.
Champion / Challenger
No calibration promotion decision.
Step 4 · Stress testing
Digital Twin
Set the assumptions on the left, then run once. The simulator models the token economy day by day and explains the result, risks and recommended changes.
ReadinessNot run
EvidenceManual inputs
ValidationNot run
Design checksNot run
Awaiting run
What happens when you run it?
The Digital Twin uses the complete blueprint selected in Optimizer sub-stages 3A and 3B, plus the Step 4 scenario assumptions on the left.
1InputsPrice, supply, allocation, vesting, users, liquidity and treasury
2SimulationDaily demand, unlocks, trading, utility, policy and stress effects
3DecisionEconomic outcome, risks, confidence and recommended controls
Real project data is optional. Without it, the run uses your manual assumptions and labels the result exploratory.
Simulation Summary
The economic outcome, main recommendation and issues requiring attention.
Recommended Design
The best candidate that passed the configured hard stops.
No recommendation available.
What limits this result
No constraints reported.
What needs attention
No critical risks reported.
Simulation Outcome
Price, liquidity, demand, unlock, treasury and policy behavior from the selected design.
No simulation result.
Economic Path
Decision Explanation
The same result explained for a selected audience.
No decision explanation available.
AI-assisted review
Use AI after the deterministic simulation to explain results, review the design or draft a report. AI does not replace the simulation.
Advanced AI actions
AI Status
Not used for this run.
AI Summary
No AI review.
Audit
No AI audit record.
Recommendations
No AI recommendations.
Generated Scenarios or Signals
No generated scenarios.
Forecast Quality
Not evaluated.
Report Draft
No draft.
Alternative optimized designs
No alternative candidates.
Token Economy
How product usage becomes token demand, and how holder behavior changes market pressure.
Utility Demand
Usage demand is shown separately from speculative trading volume.
Run the Digital Twin first.
Utility Sinks
No sink result.
Required Product Adoption
No adoption result.
Assumption Sensitivity
No sensitivity result.
Holder and market signals
Optional FOMO, panic, whale or liquidity-provider signals affect bounded cohort behavior.
Combined Behavior Effect
No signal applied.
Cohort Effects
No cohort changes.
Signal Audit
No signals recorded.
Stress Outcomes
Adversarial execution, liquidity shocks, unlock pressure and recovery behavior from the same Step 3 run.
Design guardrails
Internal utility and concentration checks. This is not legal advice.
Status
Not checked.
Utility Strength
Not scored.
Boundary
Qualified legal review remains required.
Warnings
No findings.
Required Changes
No required changes.
Market stress and recovery
Tests MEV, liquidity loss, bridge friction, whale exits and emergency policies.
Other models
Stress Outcome
No stress test.
Execution by Venue
No execution result.
Policy Response
No policy result.
Recovery Plan
No recovery plan.
Advanced Economy Models
No advanced model result.
Data evidence details
Optional technical detail showing which external records supported the run.
Available Evidence
Manual assumptions only.
Provider Details
Connections not tested.
Contracts
No contract profile loaded.
Automatic Refresh
Not enabled.
Saved Data
No saved snapshots.
Compare Designs
Save the current run, change assumptions, rerun, and compare the economic outcomes.
Saved Runs
No saved runs.
Differences
Select two saved runs to compare.
Advanced version controls
Export Results
Download the simulation configuration and approved vesting, utility, liquidity and policy settings.
Download Packages
No export generated.
Included Files
Generate an export to inspect its files.
Analysis output
Completed
Simulation Results
Economic outcomes, uncertainty and decision support from the current run.
Economic interpretation
What the simulation means
Run the Digital Twin to produce an interpretation.
Forecast range
Uncertainty, not a point promise
Model quality
Evidence and reproducibility
Decision readiness
Why this result can or cannot be acted on
Decision actions
What to change before the next run
AI-assisted review
Grounded analysis of this exact run
The AI can interpret results and propose bounded reruns. It cannot change observed evidence, compliance outcomes or the selected design.
No AI review generated. Deterministic findings above remain available without an LLM call.
Supply
Unlocks, circulation and staking
Product economy
Utility demand and adoption
Treasury
Runway and policy capacity
Execution
Liquidity and market quality
Loss attribution
What created downside pressure
Policy log
What actually activated
Lineage
Evidence, design and model traceability
Technical audit data and legacy composite
Step 1 · Project & Data
Set up the project once
Confirm the token identity and optionally connect real-world evidence. Every later model inherits this exact context.
Current stage
Ready for inputs
What you provide
- Name, token status and category
- Symbol, chain and optional objectives
- Optional public identifiers or audited files
What the engine does
- Resolves project and asset identity
- Normalizes available provider evidence
- Creates an immutable, provenance-tagged snapshot
What you receive
- Confirmed project context
- Evidence coverage, gaps and conflicts
- Pinned snapshot for all quantitative stages