If you’re new to tech startups, especially in healthcare, you might wonder: How can a small team handle massive medical data and build smart AI without a huge budget or giant server room? The answer is simple: the cloud.
At PAICON, we use a cloud platform like Amazon Web Services (AWS), as our infrastructure foundation. Think of the cloud as a giant, flexible utility - you turn it on when you need it, scale it up or down, and only pay for what you use. No need to buy expensive hardware upfront.
This article explains, in plain terms, why the cloud is perfect for a startup like ours. We’ll cover what we do, how the cloud helps, and why it matters, even if you’re not a tech expert.
What Does PAICON Actually Do?
We focus on two main things. First, we collect and organize huge amounts of medical data, such as Whole Slide Images (WSI) and accompanied Histopathology Reports from hospitals and clinics. We process this data and make it available to our industry partners which use the data for AI model training or validation.
Second, we build and test AI models for various purposes, for example for quality assurance of the medical data we ingest or for supporting medical professionals in the diagnosis.
Both tasks require a lot of storage and computing power, but not all the time. Some days we get a flood of new data. Other days, our scientists run big AI experiments. The cloud lets our system grow when busy and shrink when quiet.
Why the Cloud? It’s Like Renting Superpowers
Imagine you need a truck just once a month to move furniture. Would you buy a truck and let it sit in your driveway 29 days a month? Of course not - you’d rent one.
The cloud works the same way. Instead of buying hard drives that fill up fast, we rent unlimited storage space that grows as needed. Instead of buying servers that sit idle, we rent them by the hour and turn them off when done. And instead of paying 100,000€ upfront, we pay just 100€ only when we use it. We only pay for what we actually use. This is a game-changer for startups.
Real World Example #1: Handling New Medical Data
Every day, new medical data arrives - sometimes gigabytes, sometimes terabytes.
We run data pipelines, which are automated workflows that organize files, convert data formats, and check quality (such as spotting if a scan is blurry).
With the cloud, storage automatically expands, so there are no “disk full” errors. We start 10 or 100 computers to process data fast. When the job is done, we shut everything down. And our bill is only for the hours we ran.
No wasted money. No hardware headaches.
Real World Example #2: Training AI Models
Our AI scientists are like chefs experimenting with new recipes. They clean and prepare the data, train an AI model (which can take hours on powerful machines), and test how well it works.
Without the cloud, they’d wait days for a single computer to finish. With the cloud, they launch 20 high-powered machines at once and finish in 1 hour instead of 20. They shut everything down when done.
They can test 10 ideas in a week instead of 1. That’s how innovation speeds up.
Security: Keeping Patient Data Safe (And Legal)
Medical data is super sensitive. Laws like HIPAA in the US say: “Protect it - or face huge fines.” The cloud helps us stay safe and compliant through access controls, so only the right people or programs can see certain data. For instance, an AI scientist can only access the data that he needs for doing his job. It also uses encryption to protect data when stored or sent, and audit logs so we can prove who accessed what and when. This isn’t optional - it’s required to work with hospitals and stay legal.
Automation: Let Code Do the Boring Work
Engineers hate repeating tasks. The cloud lets us write code to manage everything, like this simple instruction: “If new data arrives, start 5 computers, run the pipeline, save results, and shut down.” We have build systems that detect when new data arrives and run the appropriate pipelines - exactly the same way, every time. This means fewer mistakes, faster setup, and more time for creative work.
Why This Matters for a Small Startup
PAICON has a small team of talented people and a limited budget. The cloud lets us handle data like a big enterprise, train AI like a tech giant, stay secure and compliant, and automate like a mature company.
