What is an AI Agent?

A working demonstration of how an AI Agent operates in an Aerospace and Defense manufacturing environment. Built around a fictional company called STRATOS Aerospace.

The Scenario

✈️

STRATOS Aerospace

Fictional company — Aerospace and Defense manufacturer

STRATOS makes structural assemblies and defense electronics for both commercial and military aircraft. Strict traceability, AS9100 compliance, and ITAR regulations mean every decision needs to be fast, accurate, and documented. This is exactly where an Agent earns its place.

Agent vs General AI

Topic

General GPT

STRATOS Agent

Knowledge source

Trained on public internet data. Knows nothing about your company.

Connected to STRATOS internal systems — traceability DB, MES, regulatory docs, NCR history.

How it answers

Generates a plausible response based on general knowledge. May hallucinate specifics.

Calls real systems, gets real data, then constructs the answer from verified facts.

What it can do

Answers questions. Cannot take actions or access live data.

Holds lots in MES, flags suppliers, drafts documents, queues follow-up tasks.

Multi-step tasks

One response per prompt. You guide every step manually.

Receives a goal, plans the steps, executes them in sequence without being prompted.

Over time

Each session starts fresh. No memory of past events unless you paste them in.

Stores events in memory. Detects patterns. Gets smarter about your specific environment.

Tools this Agent has

🗂

MES Connector

Reads and writes to the shop floor system — lot status, work orders, hold flags.

📋

Regulatory DB

Searches AS9100, ITAR, FAA, and EASA rules. Finds applicable clauses for the situation.

🔗

Traceability Engine

Traces any material or part through the full supply chain — where it came from, where it went.

📦

Supply & Inventory

Queries stock levels, supplier lead times, and certified material availability.

📝

Report Generator

Drafts NCRs, customer notifications, and corrective action reports from structured data.

🧠

Memory (RAG)

Searches past NCRs, supplier history, and prior decisions using vector similarity.

See the Agent handle a real nonconformance event, step by step.