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

Solve your systems engineering challenges

Systems Engineering processes are becoming more complex, involving more activities, standards, data, and tools.

Data spread across departments

Requirements Engineering needs to be properly digitized and fully integrated with MBSE and traceability.

Data spread across departments

Data and information need to be federated across silos, departments, tools, formats, and even organizations.

Inconsistent incomplete requirements

Incorrect, inconsistent, and incomplete models and requirements undermine quality, increase cost, and delay schedules.

Limited Capabilities

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 powered systems engineeering reuse

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.

A Unified Platform for Engineering Reuse And Control
Systems Engineering Suite (SES) platform include SES ENGINEERING Studio, SES Portal, SES Batch, and SES Add-ins

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

Step 1 - Connect your engineering tools

2. Build a semantic knowledge layer

Step 2 - Build a semantic knowledge layer

3. Automate quality, reuse, and metrics

Step 3 - Automate quality, reuse, and metrics

4. Scale across teams and programs

Step 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.

Customer

Regional Public Transport Authority, Sweden

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.​

Customer

Defense Procurement Agency, Europe

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.

Craig Brown

CIMdata

Ready to Scale Engineering Digitalization

Across Your Organization?

Join aerospace, defence, automotive, naval, railway, infrastructure, medical devices, and energy teams already using SES.