Interactive Risk-Scenario Demo

Demonstrate deterministic safety gates: drawdown limits, regime filters, and fail-closed defaults for algorithmic trading systems.

What this demo shows: This demo shows how Coerentis reacts to different risk conditions before trades reach execution. It uses simplified inputs for clarity; controlled beta systems integrate directly via API.

Note: This demo demonstrates deterministic safety gates only. No claims of profitability or trading performance.

Quick Presets

Drawdown Percent 12%

Volatility Regime

Slippage (basis points) 50 bps

Signal Confidence 75%

API Health

Kill Switch

Position Size Percent 5%

Adjust the inputs and click "Run Coerentis" to see the deterministic safety gate evaluation.

Try the Coerentis API

See how easy it is to integrate Coerentis. Enter a trade signal and see the deterministic safety gate evaluation in real-time.

Note: This is a client-side simulation demonstrating Coerentis's logic. Controlled beta systems use the REST API endpoint.

Trade Inputs

Signal

Asset

Current Drawdown -8.5%

24h Volatility 45%

Max Drawdown Limit

Max Volatility Limit

API Response

Adjust the inputs and click "Check Trade" to see the Coerentis API response.

Integration Example

Coerentis integrates with just a few lines of code:

# 3 lines to evaluate proposed exposure
from coerentis import SafetyGate

gate = SafetyGate(max_drawdown=-0.10, max_volatility=0.80)

# Before every trade:
decision = gate.check(
    signal="BUY",
    asset="BTC",
    current_drawdown=-0.085,
    volatility_24h=0.45
)

if decision.allowed:
    execute_trade()
else:
    log(f"Blocked: {decision.code} - {decision.reason}")

Integration guide