*
Sending a company's most sensitive data to a cloud service for AI analytics is like sending a postcard with trade secrets. Conveniently, yes. Are you sure? Hardly. Now that EU AI Regulation standing at the door, it's time to take home control. We show you how to build an AI powerhouse on your own terms.
It's easy to get caught up in the shark. With a few clicks in a web interface, you can have texts analyzed, reports compiled, and audio files transcribed. But beneath the polished surface lurks a critical question: Where does your data go?
For many Swedish companies and public entities, the answer is unacceptable. Legal requirements such as the GDPR, the principle of public disclosure and rock-hard confidentiality agreements put an end to the cloud. Sensitive data -- patient records, research results, customer records -- simply must not leave its own, secure infrastructure.
With the EU's new AI Regulation (AI Act) further sharpens the tone. Transparency, risk management and data protection requirements are becoming tougher. Relying on a US cloud giant's “black box” becomes a legal and business risk that few can afford to take.
Why the cloud is no longer an option
Sending data can be likened to losing control. Suddenly the information is on a server in another country, under a different law. The problems are obvious:
* GDPR & Third Country Transfer: Is your data processed in the US or Asia? Then you have probably already violated GDPR.
* Industry Confidentiality: In healthcare, law and research, local data processing is not a choice -- it is a legal requirement.
* Customer agreement: More and more procurement and customer agreements specify that all data management must take place within the walls of the organization.
* The AI Regulation: To prove that your AI use is responsible, you need to have full transparency and control. That's an impossibility with most cloud services.
The solution is as obvious as it is powerful: Run AI on your own hardware. It's the only way to guarantee 100% control, meet all legal requirements and still benefit from the huge productivity gains offered by AI.
Build Your Own AI Engine: The Hardware Required
A local AI model is no lightweight; it requires an engine capable of handling billions of calculations per second. Trying to run models like the GPT-3.5 alternative Deepseek or the Swedish models from AI Sweden on a regular office computer is like trying to tow a Finland ferry with a rowing boat. To avoid frustrating bottlenecks, a balanced machine is required:
* CPU (Processor): Think 16 cores or more. An AMD Threadripper or Intel Xeon acts as a conductor and ensures that data flows freely between the other components.
*GPU (Graphics Card): This is where the magic happens. An Nvidia RTX 4090 with 24GB of graphics memory is a solid starting point. For really heavy jobs, pro cards like the Nvidia A6000 or H100 are applicable.
* RAM (Working Memory): A minimum of 64—128 GB is needed for the model to be able to “think” and handle large amounts of data without stumbling.
* Storage: A lightning-fast NVMe Gen4 or Gen5 hard drive of at least 2TB is essential for quickly reading and writing the huge files required for document analysis, for example.
Your new digital toolbox — free and powerful
Building the engine is only the first step. You also need the tools to run it. Here are some of the best open source solutions that you can try today:
* LM Studio & GPT4all: Think of these as your personal AI library. With a few clicks, you can download and run powerful language models directly on your computer — completely offline. You can feed them with your own documents, ask questions and get answers, without a single piece of data leaving your hard drive. Ideal for those who want a private and secure chat assistant.
* Flowise: Dreaming of building your own AI app but can't code? Flowise is for you. It's like a digital Lego where you drag and drop various AI features to create bespoke tools, such as a bot that automatically sorts and responds to internal support emails.
* N8N: This is the digital superglue that binds everything together. With N8N, you can build advanced workflows where your local AI talks to your other systems. Imagine a vendor invoice landing in your inbox; N8N picks it up, lets your local AI read and extract amounts and due dates, and then creates a finished draft in the finance system for approval. Time-consuming manual buttoning is suddenly a thing of the past.
Compliq: From vision to working reality
We at Compliq have seen this development up close. We have already delivered a large number of workstations that are fine-tuned for local AI applications.
An example is the client who needed to analyze hundreds of hours of sensitive interviews. Uploading the material to a cloud service was out of the question. We built a dedicated transcription machine with a powerful Nvidia GPU and AMD processor. The result? They were able to carry out the entire process in their own, secure environment — quickly, efficiently and fully in accordance with their confidentiality requirements.
AI is no longer a distant vision of the future. It is a practical tool that can provide tremendous benefits even today, without having to compromise on security.
Are you ready to take control of your AI data?
Also read a previous article on the topic of local AI: On-premises AI models: When security means no exposure in the cloud.
Call Anders Malm at 046-38 47 73 or Bosse on +46 70-729 02 30 for a talk on how your business can become safer and smarter with local AI.
