When we think of Satellites we imagine cutting-edge technology, precision engineering, and brilliant minds at work.
What we rarely see is the chaos behind the scenes: thousands of pages of documents, conflicting requirements, scattered diagrams, and complexity that grows faster than humans can manage. Modern systems engineering isn’t just about designing hardware — it’s about managing an overwhelming flood of information.
How does GenAI Helps System Engineers Stay Ahead of Complexity?
1. Writing Better Requirements
Projects start with requirements — and often, they’re a mess. Vague sentences like “The car should drive fast” cause confusion down the line.
GenAI reviews these early, flags weak spots, and helps rewrite them clearly and precisely. This saves time, prevents misunderstandings, and reduces risk later.
2. Finding Duplicates and Patterns
Large projects mean thousands of requirement sentences. Some repeat. Some contradict.
AI analyzes this data, finds duplication, flags inconsistencies, and helps keep things clean and organized.
3. Designing System Diagrams
Once requirements are sorted, diagrams follow.
With Generative AI, engineers give simple prompts:
“Connect sensor, battery, data logger.”
AI draws it.
“Add brightness control.”
It updates.
No wasted hours redrawing from scratch.
4. RAG: Smarter Document Search for Engineers
PDF overload is real. Retrieval-Augmented Generation (RAG) lets AI search internal documents safely and quickly — no data sent to the cloud.
“What’s the max voltage?”
AI finds it. Work moves forward.
🎥 Watch the Full Session on YouTube:
Join “Building an Agentic RAG Pipeline” live at MLCon NY 2025 to see how it’s already changing the game.
