Building Logithon CaseOps: Cargo Loading Safety with UiPath Maestro Case

My first UiPath/RPA hackathon project: a cargo loading case workflow with 3D load planning, risk scoring, and human review.

tags: uipath, hackathon, automation, rpa

Building Logithon CaseOps: Cargo Loading Safety with UiPath Maestro Case

This was my first time using UiPath, and honestly, my first real introduction to RPA.

I joined UiPath AgentHack to learn by building. My project is called Logithon CaseOps, a prototype for making cargo loading safer and easier to audit.

Project link:


https://devpost.com/software/logithon-caseops

GitHub repo:


https://github.com/mongonsh/caseops

The Problem

Cargo loading looks simple from the outside: put boxes into a truck and send it.

But in reality, it can involve a lot of judgment:

• Will the cargo fit?


• Is the truck overloaded?


• Is the weight balanced?


• Is fragile cargo being stacked badly?


• Are dock photos or cargo evidence missing?


• Should dispatch continue or be blocked?


• Who approved the final plan?

A lot of this can happen through spreadsheets, messages, photos, and manual checks. That makes it hard to trace decisions later.

For a logistics team, that is risky. If something goes wrong, you need to know what happened, who approved it, and why.

What I Built

Logithon CaseOps turns a cargo loading request into a structured case.

The project includes:

• A React web dashboard


• A Node/Express API


• Cargo fit calculation


• Deterministic 3D load placement data


• Risk scoring


• Dispatch instruction generation


• A UiPath Maestro Case workflow model


• Human approval and exception stages

The idea is not just to calculate a result. The goal is to manage the whole loading decision process from intake to dispatch.

Why UiPath Maestro Case

I chose UiPath Maestro Case because cargo loading is not always a straight-line workflow.

Sometimes the case should move forward.


Sometimes it should go back for better evidence.


Sometimes dispatch should be blocked.


Sometimes a supervisor needs to approve the plan.

That matches a case-based workflow better than a simple one-way automation.

My Maestro Case model includes stages like:

1. Shipment Intake


2. Cargo Vision Review


3. 3D Load Plan Generation


4. Load Risk Analysis


5. Human Supervisor Approval


6. Dispatch Instruction


7. Evidence Rework


8. Dispatch Blocked


9. Closed

This helped me think about the business process, not only the code.

What Works

I wanted to avoid fake demo numbers, so I built real deterministic logic into the prototype.

The app can take shipment input such as truck size, cargo dimensions, quantities, and weight. Then it calculates:

• Total cargo weight


• Whether the load fits


• Placement plan data


• Risk signals


• Dispatch recommendation

The 3D load plan is generated from the actual cargo input, not just hardcoded text.

The current implementation is still a hackathon prototype, but the core calculations are real and testable.

What Was Hard

The hardest part was learning the UiPath platform while building under a deadline.

I had to understand:

• Studio Web


• Maestro Case


• Case plans


• Stage rules


• Case apps


• Human actions


• Orchestrator deployment


• How processes connect together

Some parts were confusing at first, especially around human action tasks and how case stages connect. I also ran into deployment and runtime errors while trying to make the UiPath case run end-to-end.

That was frustrating, but it taught me a lot about how real automation platforms need both good logic and good process design.

What I Learned

Before this hackathon, I thought automation mostly meant “run a script.”

After working with UiPath, I understand RPA differently.

RPA and agentic automation are not only about replacing manual work. They are also about coordinating systems, people, approvals, exceptions, and audit history.

For me, the biggest learning was this:

A useful automation is not only the action. It is the full workflow around the action.

That changed how I think about building business software.

What I Would Improve Next

If I continue this project, the next steps are:

• Deploy the API publicly


• Connect UiPath API Workflows to the backend


• Improve the case app experience


• Add more truck/container types


• Add better cargo constraints


• Add real image/evidence validation


• Make the 3D loading view more interactive


• Add stronger supervisor approval logic

The current version proves the workflow idea. The next version would make it more production-ready.

Final Thoughts

This project is not perfect, but I am proud of what I learned and built.

I started this hackathon with almost no UiPath or RPA experience. By the end, I had a working cargo safety prototype, a Maestro Case workflow, and a much better understanding of how business automation works.

If you like the idea, you can support the project in the UiPath AgentHack People’s Choice vote here:

https://devpost.com/software/logithon-caseops

Thanks for reading.