---
language: en
license: apache-2.0
tags:
- bayesian
- risk-scoring
- ai-reliability
- governance
- sre
---

# ARF Risk Scoring Model

A Bayesian risk scoring model for AI system reliability and failure prediction.  
This model implements the core risk assessment logic from the [Agentic Reliability Framework (ARF)](https://huggingface.co/spaces/A-R-F/Agentic-Reliability-Framework-API).

## 📌 Problem

AI‑driven systems fail silently in production. Without a calibrated measure of failure probability, operations teams cannot decide whether to approve, deny, or escalate infrastructure changes.

## 🔍 Mathematical Formulation

Given a set of signals (telemetry, context), the risk score is defined as:

\[
\text{Risk}(x) = P(\text{Failure} \mid \text{Signals}, \text{Context})
\]

Internally, ARF combines:
- **Conjugate Beta priors** for per‑category online updates.
- **Hyperpriors** that share statistical strength across categories.
- **Hamiltonian Monte Carlo (HMC)** to capture complex patterns (time‑of‑day, user role, environment).

The final risk score is a weighted average of these three components, with weights determined by data availability.

## 🚀 Usage

You can use this model directly via the ARF API, or integrate the underlying Python library.

### Example with ARF API (Python)

```python
import requests

response = requests.post(
    "https://a-r-f-agentic-reliability-framework-api.hf.space/api/v1/incidents/evaluate",
    json={
        "service_name": "payment-gateway",
        "event_type": "latency_spike",
        "severity": "high",
        "metrics": {"latency_p99": 350, "error_rate": 0.12}
    }
)
result = response.json()
print(f"Risk score: {result['risk_score']:.3f}")
print(f"Risk factors: {result['risk_factors']}")
print(f"Recommended action: {result['recommended_action']}")
```

### Example using the ARF Python package

```python
from agentic_reliability_framework.core.governance.risk_engine import RiskEngine

engine = RiskEngine()
risk, explanation, contributions = engine.calculate_risk(
    intent=some_intent,
    cost_estimate=100.0,
    policy_violations=[]
)
print(f"Risk: {risk}")
```

📚 Links
--------

*   **ARF Space**: [Agentic Reliability Framework (ARF) v4 API](https://huggingface.co/spaces/A-R-F/Agentic-Reliability-Framework-API)
    
*   **GitHub Repository**: [arf-foundation/agentic-reliability-framework](https://github.com/arf-foundation/agentic-reliability-framework)
    
*   **Documentation**: [API Docs](https://a-r-f-agentic-reliability-framework-api.hf.space/api/docs)
    

📊 Input / Output
-----------------

InputTypeDescriptionservice\_namestringName of the service being evaluatedevent\_typestringType of incident (e.g., latency\_spike)severitystringlow / medium / high / criticalmetricsdictTelemetry values (latency, error rate, CPU, etc.)OutputTypeDescriptionrisk\_scorefloatCalibrated failure probability (0–1)risk\_factorsdictAdditive contributions from conjugate, hyperprior, HMCrecommended\_actionstringapprove / deny / escalatedecision\_traceobjectExpected losses and variance

📄 License
----------

Apache 2.0 – See [LICENSE](https://github.com/arf-foundation/agentic-reliability-framework/blob/main/LICENSE) for details.

🤝 Contributing
---------------

Contributions are welcome! Please refer to the [contribution guidelines](https://github.com/arf-foundation/agentic-reliability-framework/blob/main/CONTRIBUTING.md) in the main repository.