dsf-quantum-sdk 2.0.1
Lightweight SDK for DSF Quantum Adaptive Scoring with IBM Quantum support
Requires Python: >=3.8
Keywords: quantum, quantum computing, ibm quantum, qiskit, adaptive scoring, hierarchical evaluation, quantum amplitude estimation, qae, dsf, decision support, machine learning

# DSF Quantum API

**Quantum-Enabled Scoring Engine for Enterprise Decision Workflows**

Hybrid classical-quantum scoring platform validated on real IBM Quantum hardware. Accelerates multi-factor decision evaluation with quantum-enhanced evaluation.

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## 🚀 Why Quantum-Enabled Scoring?

Classical scoring functions can miss non-linear patterns in complex decision spaces. DSF Quantum Scoring leverages hybrid quantum-classical techniques to:

- Quantum-enhanced evaluation under realistic noise conditions
- Compare quantum-enhanced vs classical evaluation pathways
- Accelerate multi-factor decision workflows
- Enable quantum-ready scoring infrastructure

**Designed for:** Enterprise innovation teams, advanced analytics, and decision intelligence pipelines.

---

## 📊 Use Cases

### Financial Services
- Credit evaluation workflows
- Risk assessment enhancement
- Portfolio quality analysis
- Multi-factor decision acceleration

### Insurance
- Policy evaluation
- Claims assessment workflows
- Risk stratification
- Underwriting support

### Enterprise Risk
- Vendor scoring
- Third-party evaluation
- Decision workflow optimization
- Compliance-ready assessment

### Healthcare & Life Sciences
- Patient risk stratification
- Care prioritization workflows
- Resource allocation optimization
- Clinical decision support

---

## 💼 Pricing Tiers

|      Tier        | Evaluations/Hour | Support   |   Price |
|------------------|------------------|-----------|---------|
| **Community**    |        100       | Email     | Contact |
| **Professional** |      1,000       | Email     | Contact |
| **Enterprise**   |     Custom       | Dedicated | Custom  |

---

## 🔧 Quick Start

```python
from dsf_quantum_sdk import QuantumSDK

scorer = QuantumScoring(
    api_key="your_api_key",
    license_key="your_license_key",
    tier="professional"
)


result = scorer.evaluate(
    factors=[0.85, 0.62, 0.71, 0.91],     
    weights=[1.2, 0.8, 1.5, 1.0],          
    impact_factors=[1.0, 1.3, 0.9, 1.1]    
)

print(f"Quantum-Enhanced Score: {result['quantum_score']}")
print(f"Classical Baseline: {result['classical_score']}")
print(f"Signal Quality: {result['degradation']}")
```

---

## 🎯 Platform Capabilities

**Hybrid Quantum-Classical Architecture:**  
Validated scoring function with configurable backends

**Real Hardware Validation:**  
Executes on IBM Quantum processors (ibm_brisbane, ibm_torino)

**Enterprise Integration:**  
REST API designed for pipeline integration

**Quantum-Enhanced Evaluation:**  
Non-linear pattern detection under realistic noise conditions

**Benchmark-Ready:**  
Parallel classical evaluation for comparative analysis

---

## 🏢 Enterprise Features

**Production Integration:**  
Production integration available upon completion of client validation and model governance workflows

**Flexible Deployment:**  
Hardware backends configurable per use case

**Enterprise Support:**  
Dedicated integration assistance available

**Hybrid Workflows:**  
Classical fallback with quantum acceleration options

**PoC-Ready:**  
Enterprise proof-of-concept programs available

---

## 🔒 Security

- API key authentication
- Encrypted data transport
- License enforcement per tier
- NDA available for technical specifications
- Enterprise security review support

---

## 📊 Performance Characteristics

**Validated on Real Quantum Hardware:**  
Tested on IBM Quantum production systems

**Hybrid Evaluation:**  
Quantum-enhanced scoring with classical comparison

**Configurable Backends:**  
Support for multiple quantum processors

**Signal Quality Metrics:**  
Noise-aware evaluation with quality indicators

---

## 📞 Get Started

**Request Technical Documentation:**  
Full API specifications available under NDA  
[Contact: Technical Docs](mailto:contacto@dsfuptech.cloud?subject=Scoring%20Technical%20Docs)

**Schedule Enterprise Demo:**  
30-minute consultation with your data  
[Contact: Enterprise Demo](mailto:contacto@dsfuptech.cloud?subject=Enterprise%20Demo)

**Proof-of-Concept Program:**  
Enterprise PoC with integration support  
[Contact: PoC Program](mailto:contacto@dsfuptech.cloud?subject=PoC%20Program)

---

## 📚 Resources

- [Integration Guide](mailto:contacto@dsfuptech.cloud?subject=Integration%20Guide) (requires NDA)
- [Benchmark Studies](mailto:contacto@dsfuptech.cloud?subject=Benchmarks)
- [Hardware Validation Data](mailto:contacto@dsfuptech.cloud?subject=Validation)
- [Enterprise Case Studies](mailto:contacto@dsfuptech.cloud?subject=Case%20Studies)

---

## 🔬 Built on Validated Research

Scoring engine validated on IBM Quantum hardware with documented experimental results. Suitable for:
- Enterprise innovation initiatives
- Advanced analytics workflows
- Decision intelligence enhancement
- Quantum-ready infrastructure development

Production integration available upon completion of client validation and model governance workflows.

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## 📋 Credits

**Technology Architect:** Jaime Alexander Jimenez

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