Australia 
Brazil 
Canada 
Chile 
China 
Columbia 
Denmark 
Egypt 
France 
India 
Indonesia 
Ireland 
Italy 
Malaysia 
New Zealand 
Norway 
Panama 
Peru 
Poland 
Portugal 
Saudi Arabia 
Singapore 
South Korea 
Spain 
Sweden 
Taiwan 
Thailand 
Türkiye 
United Kingdom 
United States 
Vietnam 
KEY POINTS
- AI amplifies SYSTRA’s expertise and makes our collective know-how more accessible: We believe AI will help to put the right experience, methods and technical knowledge in the hands of every team, while keeping engineers firmly in control.
- AI strengthens the quality, efficiency and reliability of our delivery: By automating repetitive work, improving project information management and supporting risk control, AI frees up time for technical judgement and higher-value work.
- AI helps us create differentiated value for our clients: From stronger commercial proposals and project delivery to new data-driven services, AI enables SYSTRA to turn innovation into concrete, useful and measurable outcomes.
In a sector facing growing complexity, SYSTRA sees artificial intelligence as an accelerator to strengthen its expertise, delivery performance and client differentiation. It helps teams explore more design options, make better use of technical and project data, anticipate risks earlier, and reduce the time spent on repetitive and information-intensive tasks.
At SYSTRA, we develop AI solutions grounded in engineering practice and designed with our domain experts by combining SYSTRA’s experience in transport and infrastructure with targeted digital capabilities. This helps to address real project needs and improve performance, quality, and delivery control.
Applied across the project lifecycle, from tendering and design to construction, systems engineering, maintenance, project governance and knowledge management, these solutions help our teams to focus their expertise on higher-value work, while turning innovation into practical, trusted and measurable benefits for our clients.
AI for Infrastructure
Infrastructure projects require early strategic decisions, often based on incomplete information, while balancing technical constraints, costs, performance objectives, and site-related risks.
In this context, AI helps teams analyse available options more quickly, make better use of existing project data, and identify design or construction risks earlier.
Optimising rail alignment
In rail design, our solution ThunderTrack supports alignment studies by generating and comparing scenarios more quickly and with greater precision. It combines topographical data, land-use constraints, the presence of rivers and bodies of water, geometric rules, cost factors, and journey-time parameters to help identify reliable alignment options from the early stages of the design process.
Exploring bridge design options
For bridge design, AI Bridge Design supports the early stages of project development by facilitating the parametric analysis of design options. Drawing on data from existing projects, this approach helps identify relevant bridge typologies, span configurations, and comparable reference structures. It helps our bridge expert to retrieve data from previous bridge design which accelerates scenario development and enriches technical analysis from the earliest stages of a project.
Managing geotechnical risks
For underground works, ReAcTIVE Tunnel and ATAS address two complementary needs in the management of excavation operations. ReAcTIVE Tunnel uses data from tunnel boring machines to monitor operations in real time, detect anomalies, and better understand ground behaviour during excavation through machine learning.
ATAS complements this approach by helping teams anticipate geotechnical risks and adapt operational control. Together, these tools help improve the performance of underground works and support on-site risk management.
VMAI, an AI Agent for automating engineering calculation and Analysis
Before a bridge, a building or a tunnel is constructed, our engineers create digital models to check its structural performance and safety. This work is essential, but much of it is repetitive: rebuilding models as designs evolve, rerunning checks and extracting and formatting results. It can absorbs a significant amount of our structural engineers’ time.
VMAI, the winning innovation of the 2026 SPARK Challenge, provides engineers with AI agents to take on this routine work. An engineer describes the task in natural language and shares the project files; the agent then works directly within the engineering software already used by the team and returns the result for the engineer to review and approve. The agents operate in a secure, isolated environment, and every exchange is traceable.
What it brings
Speed
In selected real-project applications, engineers completed work two to five times faster than by hand.
Better engineering
Time shift from repetitive modelling to design judgement, exploring more options, and responding faster to client deadlines.
Shared expertise
Each validated task becomes a reusable recipe, enabling one engineer’s know-how benefits other teams.
Always engineer-led
Nothing is used without human verification. The engineer remains fully responsible for the design.
AI for Safer and More Efficient Transport Systems
Transport systems are increasingly connected, interoperable, and data-rich. Rail, road and mobility projects must meet demanding requirements in terms of safety, reliability, maintenance, compliance and cybersecurity, often within large-scale and complex programmes.
AI helps teams make better use of this data, target priority actions, and strengthen long-term system control. Globally, the potential is particularly significant in rail: AI could generate between $13 billion and $22 billion in annual value for the railway industry (McKinsey & UIC, The journey toward AI-enabled railway companies, 2024).
Identifying road safety risks
In road safety, Collision Seek is an example of how SYSTRA uses historical accident data and geospatial information to identify collision risk factors and potential hotspots. This enables teams to prioritise targeted safety measures and take a more proactive approach to risk reducing.
Strengthening transport cybersecurity
Cybersecurity is a major challenge for transport systems, helping protect passengers, ensure business continuity and safeguard critical data and systems. Our team are exploring currently how AI can support cybersecurity experts by helping them analyse large volumes of information, identify potential vulnerabilities, prioritise protection measures and strengthen compliance processes by ensuring the quality of produced documents traceability.
AI for Decision-Making
Transport and infrastructure projects generate large volumes of technical, contractual and operational information. When this information is scattered across multiple documents and systems, processes slow down and governance becomes more difficult.
Up to 50% of tasks related to documentation and design engineering could be supported by AI (McKinsey, How AI is reshaping the future of the AEC industry, 2026). Drawing on our expertise in complex project management and advanced technologies, we help teams structure this information, reduce manual tasks, strengthen traceability and support more informed decision-making.
Supporting project management documentation
The Project Management Plan is a formal and evolving document that serves as a roadmap for how a project is executed, monitored and closed out. Using generative AI and our experience of major projects, SYSTRA can support the drafting, review and harmonisation of project management plans and associated reports. This approach helps reduce manual effort, standardise documentation and strengthen the quality of governance practices.
Managing complex project requirements
Project requirements define the technical, performance and safety criteria that are essential to the delivery of systems. To verify and manage these complex requirements, approaches such as Verify help automate certain key tasks, strengthen traceability, support compliance and improve monitoring throughout the project lifecycle.
Making project knowledge easier to access
AI-powered document intelligence can search, extract and synthesise information from large volumes of unstructured technical content. At SYSTRA, our Knower Suite helps teams and projects identify relevant knowledge more quickly, reduce the time spent searching for information and make better use of existing expertise. Where appropriate, the Knower Suite provide a secure environment to operate AI agents, helping teams access and use project knowledge while maintaining appropriate control, traceability and protection of information.
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