What's an AI Architecture, Anyway?
At its core, an AI architecture is the blueprint of all the pieces in your AI system fine-tuned to work together flawlessly. Think of it as the manual that ensures that your AI is made for your needs and ensures that the AI will work as is supposed to.
Who Needs a Private AI Infrastructure?
Private AI infrastructure is critical for organizations where data security and compliance are non-negotiable. This includes:
Law firms handling sensitive client information.
Healthcare providers managing protected health data (HIPAA compliance, etc.).
Private security agencies dealing with confidential operations.
Small to medium-sized enterprises (SMEs) required to store data locally due to regulations (e.g., GDPR in the EU) or those training proprietary AI models on sensitive data.
Not in one of these categories?
Hardware
We assume you already have some level of automation or IT infrastructure in house when you're considering AI. If not, no problem but it will cost you more. Our approach is to assess your existing tech stack and recommend only the hardware components necessary to support your AI models. This minimizes your entry costs while ensuring compatibility and performance.
Note: If you prefer not to improve your current IT infrastructure, we'll try to work with your existing infrastructure to integrate AI. However, keep in mind that AI is a new technology and it won't run on older or low performance systems.
Software
We may provide you with a software foundation for your AI system, including containerization tools (e.g., Docker, Kubernetes) if agreed upon beforehand. If needed, we can also assist in training custom AI models on your data but this will need additional compliance measures outlined in our agreement.
EU Disclaimer: Our services do not include compliance support for the EU AI Act. However, for larger projects, we can discuss integrating compliance measures as part of our agreement.
Academy
We understand that AI is a powerful tool to have but it's not as easy to navigate or use for many companies. That's why we decided to help you understand how to interact with such AI systems to get the most out of them. This includes:
Working with data in AI: Preprocessing, managing, and analyzing data for AI application/environment development.
Understanding of AI tools: Use cases, possibilities and limitations of latest AI tools/platforms.
Using Third-Party Models: Discover how to correctly use pre-trained models (e.g., from Anthropic, OpenAI, or others) for tasks like data generation, testing, or content creation.
Lightweight AI development: Learning the basic process of custom scripts modifications which enhace third-party AI model outputs for your specific needs.
Disclaimer: Wrappers are only lightweight scripts that modify or format AI model outputs. They are not AI models and rely on external APIs or services for computation. As such, they may not be suitable for organizations with strict data residency or regulatory requirements, as computations occur off-site.
Ready to work with us?