The self-hosting question
For businesses implementing AI automation — particularly those using platforms like n8n for workflow automation — the question of hosted versus self-hosted deployment arises regularly. The decision affects not just cost and control but the ongoing operational requirements of the automation.
Hosted AI: managed for you
Hosted AI services are managed by the provider. The business accesses the AI through an API or web interface and the provider handles everything else — infrastructure, updates, security, scaling.
Hosted AI advantages:
- Minimal operational burden. The provider manages the infrastructure, freeing the business from having to develop and maintain AI operations expertise.
- Always current. The provider updates models and infrastructure, ensuring the business has access to the latest capabilities.
- Scalable without intervention. The provider handles scaling, so increased usage does not require infrastructure changes on the business's side.
- Faster time to value. Hosted services can be integrated and deployed quickly, without infrastructure setup time.
Hosted AI considerations:
- Ongoing cost. Hosted services are typically priced per use, which can accumulate for high-volume applications.
- Data leaves your environment. Processing happens on the provider's infrastructure.
- Provider dependency. The business relies on the provider's continued operation, pricing and terms.
Self-hosted AI: control and cost predictability
Self-hosted AI runs on the business's own infrastructure — whether on-premise servers, private cloud or virtual private servers. The business manages the infrastructure, the models and the operations.
Self-hosted AI advantages:
- Complete data control. Data never leaves the business's infrastructure.
- Predictable cost. Once infrastructure is in place, marginal cost is low regardless of volume.
- Customisation. Self-hosted AI can be configured, modified and extended in ways that hosted services may not allow.
- No usage limits. There are no API rate limits or usage caps imposed by a provider.
Self-hosted AI considerations:
- Infrastructure management. The business needs the capability to manage servers, updates, security and availability.
- Model management. The business is responsible for selecting, deploying and updating AI models.
- Initial setup time. Self-hosted deployment takes longer to set up than hosted services.
Making the choice
The choice between hosted and self-hosted typically depends on three factors:
- Data requirements. If data must remain within your infrastructure for compliance or security reasons, self-hosting is required.
- Volume economics. If usage is high enough that hosted pricing becomes significant, self-hosting may be more economical.
- Operational capability. If the business has the capability to manage AI infrastructure, self-hosting is viable. If not, hosted services reduce the operational burden.
For a related comparison focused on infrastructure location, see cloud AI vs on-premise AI. For the model provider comparison, see OpenAI vs Anthropic for business.
Moonshot Monkeys helps businesses evaluate and implement the right deployment model for their AI automation. If you are weighing hosted versus self-hosted options, we can help you make the decision that fits your requirements and capabilities.