Service Overview

System Test AI

End-to-end automated validation that reduces testing time by up to 75% through AI-generated test scenarios and intelligent execution. Ensures ISO 26262 functional safety compliance — using graduated warning strategies and temporal plausibility checks to minimize false positives. Supports HIL, SIL, and vehicle-loop environments with a validated AI model pipeline achieving 18.7× inference speedup.

HILSILISO 26262Test AutomationAI Model ValidationAUTOSARFunctional Safety

75%

faster test execution

ISO 26262

safety compliance

18.7×

inference speedup

5.99%

accuracy improvement

49.15%

recall improvement

Capabilities

Key capabilities

End-to-End Test Automation

Comprehensive system-level testing from requirements to validation.

HIL/SIL Support

Full support for Hardware-in-the-Loop and Software-in-the-Loop testing environments.

Traceability Matrix

Complete traceability from requirements to test cases to results.

Automated Test Generation

AI generates system test scenarios based on requirements and specifications.

Performance Optimization

75% reduction in test execution time through intelligent test scheduling.

Technology

Technology stack

Component Technology
Test Framework AUTOSAR, CANoe
Simulation MATLAB/Simulink, CarMaker
Test Generation LLM, AI models
Traceability Requirements management tools
CI/CD Jenkins, GitLab CI

Use cases

Real-world applications

Documented outcomes from actual deployments.

1

Accelerated Test Generation

AI automatically generates test cases from models and requirements, replacing the 20–40 minute manual process with a 5–7 minute AI-powered workflow at 85–90% accuracy.

Before

20–40 minutes manual test case creation per task, 1–2 month testing phases

After

5–7 minutes AI generation per task, 0.5–1 month testing phases

5–7 min vs 20–40 min manual
30–40% cycle reduction
2

AI Model Validation Pipeline

Three-stage validation pipeline (AI Model Loop → Hardware Loop → Vehicle Loop) to validate AI models for automotive applications within tight production timelines, ensuring both performance targets and functional safety are met.

Before

No structured pipeline to validate AI models against rigorous automotive performance criteria

After

Both AI models deployed and exceeded production targets on schedule

5.99% accuracy improvement
18.7× inference speedup

How we work

Implementation approach

1

Phase 1: Requirements Analysis

  • Analyze system requirements and specifications
  • Define test scenarios and acceptance criteria
  • Plan HIL/SIL test environment setup
2

Phase 2: Test Generation & Automation

  • Generate system test cases from requirements
  • Automate test execution in HIL/SIL environments
  • Create traceability matrix
3

Phase 3: Validation & Optimization

  • Execute tests and validate results
  • Optimize test execution order and scheduling
  • Ensure comprehensive requirement coverage
4

Phase 4: Continuous Integration

  • Integrate with CI/CD pipeline
  • Automate regression testing
  • Monitor test results and quality metrics

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