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QUANTUM INTELLIGENCE TECHNOLOGY

Engineering the Quantum–AI systems that will power the next generation of industry.

QIC develops Quantum–AI technologies that bring quantum computing into high-value industry applications. We combine advanced quantum methods, artificial intelligence and deep domain expertise to expand how complex problems can be understood, computed and solved.

01 / Why Quantum–AI Hybrid

Complex industry problems demand a new computational approach.

AI is highly effective at learning from data, recognizing patterns and making predictions. Quantum computing introduces fundamentally different approaches to selected problems involving molecular systems, high-dimensional structures, probabilistic estimation and combinatorial search.

ARTIFICIAL INTELLIGENCE

AI learns from
complexity.

AI extracts patterns from complex data, supports prediction and helps identify the most relevant structure within a problem.

1How AI works
Technology | QIC
DataStructured & unstructured
LearningPattern extraction
PredictionInference & generation
2Where AI excels
Technology | QIC
Pattern recognition
Technology | QIC
Classification
Technology | QIC
Recommendation
Technology | QIC
Generation
QUANTUM COMPUTING

Quantum expands the
computational frontier.

Quantum methods introduce new ways to represent and explore selected problems in learning, simulation, estimation and optimization.

1How quantum computing works
Technology | QICALGORITHM EXECUTION
State preparationEncode the problem into quantum states
Quantum computationExecute quantum operations defined by the algorithm
MeasurementCollect classical outcomes from quantum states
2Where quantum methods can contribute
Technology | QIC
Molecular interactionAI limitationElectronic-level behaviour is difficult to represent from data alone.
Technology | QIC
Electronic structureAI limitationAccurate calculation becomes costly as molecular complexity grows.
Technology | QIC
Complex optimizationAI limitationThe search space can grow faster than exhaustive exploration allows.
Technology | QIC
Quantum-system simulationAI limitationQuantum behaviour is difficult to reproduce with classical approximation alone.
DOMAIN-DRIVEN HYBRID WORKFLOW
Technology | QICData · objective · constraintsAI & classical analysisSelected quantum computationIntegrate & validateREFINE THE MODEL · TEST AGAINST EVIDENCE

QUANTUM–AI HYBRID

QIC turns convergence into industry capability.We design the combination around the structure, constraints and value of real industry problems.

How QIC builds the hybrid layer

  1. Problem mappingStructure & transformation
  2. Quantum layerSelected computation
  3. Result fusionIntegration & validation
Quantum methods are selectively applied to these computational bottlenecks—then integrated with AI and validated against real outcomes.
AI FOR QUANTUM

Across the quantum field, AI can support system design, control, optimization and practical operation.

QUANTUM FOR AI

Quantum methods may extend selected capabilities in learning, molecular calculation, probabilistic estimation and optimization.

QIC’s focusTranslate this convergence into industry-specific systems, validated against domain outcomes.

02 / QIC HYBRID METHODOLOGY

QIC’s core competency is turning the right industry problem into the right Quantum–AI system.

Across each industry and domain, QIC identifies the problem worth solving, isolates the computational bottleneck and determines which technical methodology and quantum algorithm—combined with AI—best fit the objective, data, constraints and validation requirements. This accumulated methodology and know-how form a core part of QIC’s technological capability.

01

Define

Which problem in which industry or domain can create meaningful value?

Define the objective, domain data, operational constraints and validation criteria.

02

Decompose

Where does the critical computational bottleneck occur?

Decompose the full problem and isolate the segment limited by scale, complexity, physical modelling or uncertainty.

03

Design

Which technical methodology and algorithm are most appropriate?

Compare AI, established optimization, quantum-inspired methods and quantum algorithms; then design the quantum mapping, variables, objectives and circuit.

04

Integrate

How should AI and quantum computation work together?

Assign clear roles to AI analysis, problem reduction, quantum computation and result integration within one hybrid system.

05

Validate

Does the system create measurable industrial value?

Compare accuracy, performance, stability and operational value with established methods, experimental data and real outcomes.

The methodology is adapted to each domain and problem; it is not a fixed technical sequence applied identically to every use case.

03 / METHODS & ALGORITHMS

Different industry problems require different quantum algorithms.

QIC selects and combines quantum algorithms according to each problem’s objective, data structure, computational bottleneck and validation requirements.

QML / CONCEPTUAL WORKFLOW
Technology | QICINPUT VECTORx1x2x3x4ENCODINGFEATURE REPRESENTATION

A conceptual data encoding into a quantum feature representation.

Research reference ↗
Research & Validation

Quantum Machine Learning

PROBLEM STRUCTURE
High-dimensional classification and prediction
TECHNICAL ROLE
Explore complex patterns and decision boundaries using quantum feature spaces and hybrid learning models.
FintelliQ™Credit assessment · anomaly detection

Performance is evaluated against established methods and available hardware.

QIC does not assume that quantum computation is the best answer to every problem. Each algorithm is assessed against established alternatives, available hardware, data conditions and expected industry value.

04 / TECHNOLOGY ROADMAP

Designed for today’s hybrid environment—and the capabilities ahead.

Current hybrid validation and future quantum capabilities have distinct roles in QIC’s development path.

01TODAY

Hybrid &Validation

Build and validate systems using AI, domain models, quantum-inspired approaches and selective NISQ experiments.

  • Industry PoC
  • Baseline comparison
  • Selective quantum experiments
02NEXT

Expanded HybridApplication

Expand problem mapping and system integration as hardware, circuits and hybrid workflows improve.

  • Broader problem scope
  • Improved workflow reliability
  • Enterprise integration
03FUTURE

Fault-TolerantQuantum Computing

Address more complex molecular, optimization and estimation problems as fault-tolerant capability develops.

  • Advanced molecular simulation
  • Larger optimization problems
  • New industry use cases

Progress depends on hardware, error control and the requirements of each application.

05 / FROM TECHNOLOGY TO INDUSTRY

One methodology, applied to distinct industry problems.

QIC’s technology becomes valuable when it is integrated with domain knowledge, real data and measurable industry outcomes.

DRUG DISCOVERY

QUEST™

Molecular analysis→Candidate evaluation→Experimental validation

Hybrid technology for candidate discovery, molecular analysis, preclinical prediction and proprietary drug development.

Explore QUEST™ ↗Proprietary pipeline ↗

FINANCIAL INTELLIGENCE

FintelliQ™

Risk prediction→Constrained optimization→Decision validation

AI and optimization methods for credit assessment, ruleset design, portfolio problems and financial decision support.

Explore FintelliQ™ ↗Industry PoC ↗

EXPLORE QIC TECHNOLOGY

Quantum capability, engineered for industrial value.

Explore how QIC applies Quantum–AI technology to drug discovery and financial intelligence.

Discuss a collaboration ↗