SES: An ALM for Connected Systems Engineering
Manage requirements, models, traceability, interoperability, quality, verification, validation, SE measurement, and reuse of engineering knowledge in a single platform, while maintaining connectivity with your tools ecosystem
Solve your Systems Engineering challenges using SES
Systems Engineering processes are becoming more complex, involving more activities, standards, data, and tools.
Requirements Engineering needs to be properly digitized and fully integrated with MBSE and traceability.
Data and information need to be federated across silos, departments, tools, formats, and even organizations.
Incorrect, inconsistent, and incomplete models and requirements undermine quality, increase cost, and delay schedules.
High complexity and manual effort are required to establish an SE lifecycle measurement baseline.
Teams spend more time searching, fixing, moving, and recreating data than engineering
Solutions for two different domains
FOR SMALL AND MEDIUM-SIZED ENTERPRISES
Digitalize your Systems Engineering processes
- Author and manage requirements
- Model requirements and systems with SysML v2
- Manage engineering knowledge and documentation
- Support quality, traceability, and verification workflows
FOR LARGE ENTERPRISES
Connect your Systems Engineering ecosystem
- Connect engineering tools and enable interoperability
- Establish traceability and a digital thread across artifacts
- Analyze the quality of requirements, models, and documents
- Connect with your OEM’s/TIER’s tools and collaborate
Think big, start at the right level, and mature
SYSTEMS ENGINEERING
Capabilities
Requirements Management
Manage, analyze, and reuse engineering requirements throughout the system lifecycle. Improve requirements writing, quality, consistency, and traceability while supporting better-informed engineering decisions.
Model-Based Systems Engineering
Create and manage SysML v2 system models to represent architecture, system behavior, and engineering relationships. Merge models with requirements, improve model quality, and maintain consistency between models and other engineering information.
Quality, Verification and Validation
Assess the quality of requirements, models, and engineering documents. Support verification and validation processes by identifying inconsistencies, checking compliance, and providing evidence that engineering outputs meet their intended needs.
Traceability & Digital Thread
Define a complete and integral digital thread approach by enabling universal traceability. Eliminate information silos and connect models, requirements, test cases, documents, risks, decisions, lessons learned, etc.
Connectivity & Interoperability
Connect engineering tools and exchange information across heterogeneous environments. Enable consistent data interpretation, semantic interoperability, and the integration of engineering knowledge across tools, teams, and organizations.
Systems Engineering Measurement
Define and apply systems engineering measures to assess product, process, and project performance. Turn engineering data into objective indicators that support decision-making, progress monitoring, and continuous improvement.
Systems Engineering Digitalization with SES
To manage the rising complexity of Systems Engineering activities, organizations need integral digital solutions that break down information silos and streamline lifecycle processes.
AI & ENGINEERING KNOWLEDGE
An AI Platform for Systems Engineering Digitalization
SES brings engineering information and data from your tools into one semantic layer. AI uses that shared context to support reuse, quality assurance, interoperability, and measurement.
AI works with the knowledge already in your engineering environment.
THE SES ECOSYSTEM
Powered by the Systems Engineering Suite (SES)
An AI-enabled platform for engineering lifecycle management, reuse, and interoperability.
- ALM and MBSE digitalization
- Tool ecosystem integration
- Semantic knowledge base
- AI-powered automation
- Lifecycle traceability and interoperability
- Systems Engineering measurement
Deploy Without Disrupting Your Tools, Just Solving Existing Problems
1. Connect your engineering tools
2. Build a semantic knowledge layer
3. Automate quality, reuse, and metrics
4. Scale across teams and programs
Do you already have an SE tools ecosystem? ⇒ No tool replacement required
Designed for Systems Engineering - from simple beginnings to high complexity
Trusted by engineering teams in aerospace & defense, automotive, railway, energy, and telecommunications. Supports ISO 15288 compliance, MBSE, and Digital Engineering.
We typically set aside 6 months for appeals from competing bidders after awarding a Contract. This time, there were no appeals due to excellent quality, traceability, and transparency in the Acquisition Phase. The project could start immediately after Contract Award.
We have successfully used RQA – QUALITY Studio to analyze and track requirements quality over time in different defense acquisition projects. SES ENGINEERING Studio and Acquisition Studio are being used with DOORS RM DB to manage requirements and systems engineering tasks from RFQ preparation to verification and validation, including supplier data exchange, bidder evaluation, negotiations, and contracting.
Effective system engineering needs to have an interoperability framework that removes confusion and ambiguity. The REUSE Company’s SES ENGINEERING Studio is such a framework.
Ready to Scale Engineering Digitalization
Across Your Organization?
Join aerospace, defence, automotive, naval, railway, infrastructure, medical devices, and energy teams already using SES.