At the heart of any IT solution is its infrastructure, which includes the hardware and software necessary to run it.
For example, machine learning model training requires a dedicated machine, and to speed up the process, multiple machines and management software are needed to distribute the workload. Without infrastructure, there’s no solution.
Infrastructure is a core component of any IT solution and is therefore part of every use case. Let's highlight some of the types of infrastructure we have experience with:
This is our bread and butter. We use this infrastructure to train, verify, deploy and serve new machine learning models.
This type of infrastructure is built around the concept of real-time events. This means that every change in a database is captured and published to other systems, which can then react to it.
Not every solution can be run entirely in the cloud. We have, however, set up infrastructures that can use the cloud's scalability for training ML models while serving those models on-premise.
Since infrastructure depends on the specific use case, we typically build our own infrastructure in the cloud.
However, because Paperbox is an expert in this area, we occasionally use their infrastructure for document processing.
For edge deployment, we collaborate with other parties to make sure everything runs smoothly and meets uptime requirements.