Dependency on Suppliers
When you develop AI solutions on large cloud platforms like AWS, Google Cloud, or Microsoft Azure, you run the risk of getting stuck in what we call "vendor lock-in." This means you become dependent on a single provider for the infrastructure and management of your AI systems. At first glance, this might not seem like a problem, but in the long run, it can limit your flexibility and control while significantly driving up costs.
What is vendor lock-in?
Vendor lock-in occurs when your AI solutions become so closely tied to the technology of a specific cloud provider that switching to another vendor becomes difficult, time-consuming, and expensive. Many cloud platforms use proprietary tools and standards that are not easily transferable to other systems. This makes migrating to another platform a technical challenge, often accompanied by high costs for rebuilding or adjusting your AI infrastructure.
Limited control over your AI systems
Another issue with developing AI in the cloud is the limited control you have over the underlying infrastructure. Cloud providers manage the hardware and systems on which your AI models run, and you must operate within their limitations. This can affect how you want to configure and adapt your AI solutions to meet the specific needs of your business. Flexibility is often restricted, making it challenging to implement customized solutions that align seamlessly with your business processes.
In some cases, changes in the services or pricing models of a cloud provider may force you to reconsider your AI strategy, as you have no direct influence over how the infrastructure is managed. This leaves you vulnerable to unexpected price increases or changes in service terms, which can impact your company financially.
Local AI solutions: Full control and flexibility
With local AI solutions, you eliminate this dependence and the associated limitations. You have full control over your own infrastructure and how your AI models are managed. You can choose your own hardware, decide on configurations, and ensure that everything is perfectly aligned with the unique needs of your organization.
In addition, local AI offers much more flexibility when it comes to customization. You can adjust, optimize, and integrate your systems with other tools and technologies without being tied to the restrictions of a cloud provider. This makes it easier to evolve your AI solutions quickly and adapt to changing business conditions without relying on the updates or choices of an external vendor.
Avoid high migration costs
By opting for local AI, you avoid the high costs and technical challenges associated with switching to another cloud platform. Once you're locked into a vendor, migrating your AI systems to another provider can be a costly and time-consuming task. This often involves redeveloping parts of your infrastructure, which requires both resources and specialized knowledge. With local AI solutions, you don’t face these issues. You are free to adjust and optimize your infrastructure at your own pace and on your own terms, without being dependent on external parties.
Choose future-proof AI with full freedom
By investing in local AI solutions, you not only ensure the flexibility and scalability of your AI systems, but you also avoid being locked into a specific vendor. This means you are always free to integrate new technologies or other tools without restrictions or unexpected costs. You retain full control over your data, your infrastructure, and your budget.
With local AI solutions, you ensure that your company remains agile and able to respond to changes in the market without the limitations of a cloud provider. You decide how your AI grows and evolves, giving you a strategic advantage.
Want to know more about how local AI solutions can help your business?
Contact us today to discover how we can support you in building flexible, scalable, and future-proof AI solutions tailored to your needs.
