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AI Testing for Mission-Critical Systems

AI systems deployed in defence, public safety, and critical civil use cases must meet a higher bar for performance and reliability.

Our testing processes are designed to uncover edge-case risks, operational blind spots, and safety concerns before they impact the field. These use cases show how we help validate AI systems under stress, uncertainty, and evolving real-world conditions — where failure is not an option.

1.

Facial recognition

Facial recognition systems are tested to ensure they work accurately across different faces and settings, and are not easily fooled. Testing helps reduce bias, avoid errors, and build confidence in real-world use, especially in high-security environments.

2.

Object detection

Object detection systems are tested to evaluate how well they identify and track items such as vehicles, people, or threats in dynamic or cluttered environments. This supports situational awareness in warehouses, perimeter defence, and security screening.

3.

Medical imaging

AI used in medical imaging is tested to check whether it consistently supports accurate diagnosis. This includes assessing how the system performs across different types of scans, patient cases, and clinical conditions.

4.

Chatbot

AI chatbots used in customer interactions and critical decision planning systems are tested to ensure they deliver clear, trustworthy, and safe responses — even under stress or ambiguous user input.

5.

Document Generation

Document generation AI is tested to verify that critical information — such as field reports, security summaries, or official notices — is generated accurately, consistently, and without introducing risk or misinformation.

6.

Agentic workflows

AI agents operating in mission planning or autonomous decision support are tested to ensure they follow intended protocols and do not take unintended actions, reducing operational risk in complex environments.

7.

Deepfake Detector Evaluation

Deepfake detection systems are tested with manipulated content to ensure they can reliably detect threats to media integrity, including misinformation targeting public trust, national security, or high-profile individuals.

8.

Autonomous Perception

Autonomous perception systems are tested to confirm they can safely interpret surroundings in unpredictable environments, such as on patrol, in reconnaissance drones, or during unmanned ground operations.

9.

Counterdrone

Counter-drone AI is tested in live and simulated airspace scenarios to evaluate how effectively it detects, classifies, and responds to unauthorised or hostile drones, protecting critical sites and restricted zones.

Harnessing the Best of Both Worlds

Singapore‘s innovation dynamic with European excellence in trust and governance

We specialise in mission-critical AI use cases. Our expertise spans jurisdictions and industries. We bridge innovation across civil and defence use cases.

Get in touch with us or start your evaluation now.