Artificial intelligence serving compliance, safety and reliability
Case study: CertX and CS Group
Are you active in the electric and smart transport sector, whether in the zero-emission vehicle industry, charging infrastructure or batteries?
Discover how artificial intelligence is becoming a strategic lever for accelerating certifications, strengthen reliability of systems and ensure compliance of technologies at the heart of the energy transition.
Artificial intelligence (AI) has today established itself as an undeniable tool to improve system performance, quality and reliability in areas as sensitive as transportation.
However, its integration raises a major challenge: how to guarantee the safety and compliance of these technological solutions?
This study presents two concrete examples that answer this question:
- CertX, an auditing and certification body that uses AI to make its assessments more efficient, complementing human expertise.
- CS Group, an engineering company that integrates AI into critical systems (such as autonomous vehicles) and develops methods to ensure their reliability.
Their testimonies demonstrate how AI can make technological solutions faster, more reliable and more accessible, while contributing to building a sustainable and safe industrial ecosystem.
CertX: Automating audits to strengthen compliance through AI
CertX is a Swiss company founded in 2018 that recently arrived in Quebec. It specializes in certification in functional safety, cybersecurity and artificial intelligence.
Its role is to support industrial companies, notably those in zero-emission transport, which must comply with increasingly demanding quality and safety standards.
The certification audits conducted by CertX rely on long, repetitive manual analyses: thousands of pages of documentation, tests and data to verify.
This significant workload slows down processes and limits CertX's capacity to effectively support its clients, in a context where the development of new products supporting the energy transition requires moving faster without compromising safety.
To make its audits faster and more accurate, CertX is developing a solution that integrates artificial intelligence algorithms into its assessment tools in order to analyze data, identify potential non-conformities and prioritize points to check.
But unlike some automated approaches, the human remains at the center:
- Auditors validate and interpret the results provided by the AI;
- They integrate new norms and standards as soon as they are published;
- They retain final responsibility for certification decisions.
AI therefore supports, rather than replaces, human expertise.
Expected results and impacts
- efficiency gain : audits are faster and more targeted;
- greater reliability : the detection of deviations is more consistent and documented;
- empowerment of auditors : they devote more time to analysis and strategy;
- strengthening of trust of industrial clients, notably in the transport, energy and electric mobility sectors.
CertX illustrates how AI, well integrated and governed, makes it possible to do more and better, while retaining the rigor necessary for certification.
CS Group: Integrating and ensuring the reliability of AI in critical systems
CS Group is an international player specialized in critical embedded systems, with over 25 years of presence in North America in demanding sectors such as intelligent mobility, aerospace, defense and rail.
Historically, CS Group has built a reputation around high-reliability embedded systems engineering, supported by a Safety First culture and a constant pursuit of engineering excellence. This expertise in the design and validation of critical software forms the foundation on which the company is now integrating artificial intelligence into its engineering activities, in order to automate complex tasks, improve software quality and accelerate development cycles.
In the context of zero-emission transport, CS Group is particularly interested in autonomous driving technologies and the contribution of AI to strengthening the safety, efficiency and performance of embedded systems.
One of the major challenges related to critical embedded systems, such as those found in electric vehicles, charging stations or intelligent transport solutions, concerns software validation, a step that can represent up to half of development costs. To make this process more efficient, CS Group designed a tool based on artificial intelligence.
The project began in 2018 and was then tested on real projects from 2022, in partnership with CRIM as part of a research and development initiative.
The team had to tackle several challenges:
- The heterogeneity of vocabulary and data formats : each company has its own way of structuring and naming information, which makes the use of generic AI tools difficult. To remedy this, the team developed a data generator capable of enriching and augmenting training datasets;
- Data anonymization : essential to protect confidential information, it however reduced vocabulary diversity and led to interpretation errors. CS Group implemented specific treatments, adjusted anonymization strategies and correspondence dictionaries in order to maintain the reliability of the results;
- The rapid evolution of AI technologies : the tool was initially built on traditional language models (NLP, then pre-generative LLMs like GPT-J or BERT), quickly overtaken by more recent models such as GPT-4. Maintaining the performance of a cutting-edge tool requires continuous investment and constant technological monitoring.
Results and outcomes
Concretely, the tool reads the specifications, automatically generates test scenarios and scripts. The results are significant:
- from 20 to 30% productivity gain;
- a reduction in human errors;
- an improvement in software quality;
- while retaining a human supervision to ensure the compliance and safety of critical systems.
After integrating artificial intelligence into its engineering activities, CS Group had to answer a key question: how to ensure that AI algorithms remain reliable and safe, whether they are used for system design or directly integrated into critical functions of intelligent mobility?
For this, the company developed a governance framework ensuring that each algorithm meets the safety, robustness and transparency requirements of international standards, including ISO 26262. In practice, and to put it simply, this framework is based on three main components:
- Identify and prevent dangerous situations by anticipating moments when the AI goes beyond its comfort zone, triggering safe fallback behaviors;
- Verify the quality of training data by ensuring they are complete, accurate and consistent with real-world operating conditions, in order to clearly define when the AI can operate safely;
- Provide robust and transparent evidence by demonstrating how the AI was designed, trained, tested and validated, in order to ensure the trust of certification authorities and end customers.
It also paves the way for applications in the zero-emission mobility, for example in:
- the intelligent battery management;
- the predictive maintenance;
- or even the automated management of charging infrastructure.
Conclusion
Artificial intelligence is profoundly transforming how companies design, verify and certify their technologies.
CertX and CS Group demonstrate that AI is not only an automation tool, but a driver of trust and efficiency.
- At CertX, it will enable the faster certification of cutting-edge technologies;
- At CS Group, it allows the automation of engineering activities (software development and verification) but also provides new guarantees on the reliability of algorithms incorporating AI (ML) used in intelligent mobility, with the aim of accelerating the certification and commercialization of advanced technologies.
These two approaches show how AI can strengthen the performance of zero-emission transport sectors, while respecting the imperatives of safety, transparency and sustainability.
AI in the service of ethics
However, artificial intelligence cannot be deployed without reflection on its responsible use .
Like any powerful tool, it must be used with discernment:
- by respecting the data protection ;
- by ensuring the transparency of decisions ;
- and by keeping the human at the heart of processes.
It is equally important to ensure that the use of AI is aimed at increasing collective well‑being. Furthermore, considering its significant energy use, it should be used while reducing its environmental impact as much as possible and only when it can have a real positive impact.
AI ethics is not a constraint, but a essential condition for its use .
There are resources to support transport stakeholders toward a ethical, reliable and sustainable AI.
- The Montreal Declaration is addressed to policymakers as well as to any person, any civil society organization and any company wishing to participate in the responsible development of AI. It lists principles that form the directions of an ethical compass to guide the development of artificial intelligence toward morally and socially desirable ends.
- Here is also a resource offered by the Ordre des ingénieurs du Québec . This document presents a synthesis of the 6 areas of vigilance of the Professional Practice Guide, highlighting the recommendations of the Ordre des ingénieurs du Québec on the responsible use of artificial intelligence.
We encourage you to adopt a thoughtful and responsible approach in your use of artificial intelligence. The resources we offer below are not exhaustive; we therefore invite you to deepen your knowledge and remain attentive to best practices regarding ethical AI.
