• Written by Azhar Aliyar, Director

A data architect sits at her desk, staring at the purchase order table on her screen, trying to decide whether to deploy AsscherAi on premise or in the cloud, a decision that will affect how her organisation queries its own data in real time. The choice between on premise or cloud for enterprise AI is not just about data residency, but about the underlying infrastructure and its implications.

What each option genuinely commits you to

The on premise option commits you to maintaining and updating the hardware and software infrastructure, which can be time-consuming and require significant resources. This includes ensuring the security and integrity of the data, as well as managing the scalability of the system. On the other hand, the cloud option commits you to relying on a third-party provider for the infrastructure, which can raise concerns about data sovereignty and security. The cloud provider will be responsible for maintaining and updating the infrastructure, but this also means that the organisation has less control over the underlying systems.

In the case of AsscherAi, the on premise option would require the organisation to have a dedicated team to manage the infrastructure, whereas the cloud option would allow the organisation to focus on using the platform to query its own data. The choice between on premise or cloud for enterprise AI is not just about the initial deployment, but about the ongoing commitment to maintaining and supporting the system.

The case where the other one is right

There are cases where the cloud option is the better choice, such as when the organisation has limited IT resources or requires a high degree of scalability. In these cases, the cloud provider can offer a more flexible and scalable infrastructure, allowing the organisation to quickly deploy and use AsscherAi. On the other hand, there are cases where the on premise option is the better choice, such as when the organisation has sensitive data that cannot be stored in the cloud or requires a high degree of control over the infrastructure.

A shift supervisor at a manufacturing plant, for example, may require access to real-time data on the production line, which would be better supported by an on premise deployment of AsscherAi. In contrast, a category manager at a retail company may be able to use a cloud-based deployment of AsscherAi to compare suppliers and optimize inventory levels.

The cost that only shows up later

One of the costs that only shows up later is the cost of integrating AsscherAi with existing systems and infrastructure. This can be a significant cost, especially if the organisation has a complex IT landscape. The cost of integration can be higher for on premise deployments, as the organisation will need to ensure that the system is compatible with its existing infrastructure. However, the cost of integration can also be higher for cloud deployments, as the organisation will need to ensure that the system is compatible with the cloud provider's infrastructure.

Another cost that only shows up later is the cost of supporting and maintaining the system. This can include the cost of training IT staff, as well as the cost of upgrading and updating the system. The cost of support and maintenance can be higher for on premise deployments, as the organisation will be responsible for maintaining and updating the system. However, the cost of support and maintenance can also be higher for cloud deployments, as the organisation will need to pay for ongoing support and maintenance from the cloud provider.

A way to decide without a six month evaluation

One way to decide between on premise or cloud for enterprise AI without a six month evaluation is to start with a small pilot project. This can help the organisation to test the system and determine which deployment option is best for its needs. The pilot project can also help the organisation to identify any potential issues or risks associated with the deployment option. For more information on how to get started with a pilot project, visit our website.

Another way to decide is to consider the organisation's overall IT strategy and goals. If the organisation is already invested in a cloud-based infrastructure, then a cloud-based deployment of AsscherAi may be the better choice. However, if the organisation has a strong preference for on premise deployments, then an on premise deployment of AsscherAi may be the better choice. To discuss your organisation's specific needs and goals, contact us at contact-us.

What this does not do

This article does not provide a definitive answer to the question of whether on premise or cloud is the better choice for enterprise AI. The answer will depend on the specific needs and goals of the organisation, as well as its overall IT strategy. What this article does provide is a framework for considering the pros and cons of each option and making an informed decision.

Most people get wrong the idea that the choice between on premise or cloud for enterprise AI is a simple one, and that one option is always better than the other. However, the reality is that the choice between on premise or cloud for enterprise AI is complex and depends on a variety of factors, including the organisation's IT infrastructure, its data residency requirements, and its overall goals and strategy.