Comparison
Hosted AI vs Self-Hosted AI Models for ERP Data
Hosted AI or self-hosted AI models for ERP data? Compare privacy, quality, cost and effort, and what to ask before you choose.
Short answer: hosted AI services give stronger models with almost no setup, while self-hosted models keep prompts on your own servers at the cost of effort and usually of quality. Pick by how sensitive the data is and how much quality you need, and send only the records a task actually needs.
The question from the security officer
A company turns on an AI assistant in its ERP and staff love it. A week later the security officer asks a simple question: when someone asks the assistant about a customer, where does that customer's data go?
Nobody has an answer. The data goes to an AI provider's servers, under that provider's terms, for as long as those terms allow. The assistant is still useful, but now the company needs to decide, deliberately, which information may travel and which must not.
The problem
AI in business software almost always means sending text to a model. The model may run at a provider you do not control, or on a server you do. That one fact decides your privacy position, your costs and the quality you get.
The mistake is treating it as an all-or-nothing choice. Different tasks carry different sensitivity: drafting a public-facing email is not the same as summarising a payroll run.
- Nobody can say what data an assistant sends out.
- A provider's data terms are unread or unclear.
- Usage costs grow with no cap.
- A rule or customer contract limits where data may go.
The options side by side
| Hosted AI service | Self-hosted model | |
|---|---|---|
| Setup | An account and a key. | Servers, a model and upkeep. |
| Quality | Typically strongest. | Depends on the model and hardware. |
| Where prompts go | To the provider. | Stay on your servers. |
| Cost shape | Pay for what you use. | Hardware and people, then little per request. |
| Speed and scale | Provider's capacity. | Your capacity. |
| Good fit | Drafting, research, general questions. | Sensitive data or strict data rules. |
Hosted AI services
A hosted service needs only an account and a key, and gives you some of the strongest models without any hardware. You pay for what you use and scale without planning.
Your prompts travel to the provider, so you must read its terms on storage and training, send only what a task needs and cap spending so a busy month cannot surprise you.
Self-hosted models
A self-hosted model runs on your own server. Prompts never leave your network, which answers the privacy question completely and satisfies strict data rules.
In return you take on hardware, setup and upkeep, and open models that fit a modest server are usually weaker than the strongest hosted ones. Good for focused tasks, less so for demanding ones.
How to decide
Sort your AI tasks by the sensitivity of their data first.
- What data would the model see, and could less be enough?
- Does the provider keep prompts, and for how long?
- Who pays for usage and how is it capped?
- Can you switch provider without rebuilding?
- Do you have the skills to run a model server?
The solution: a practical path
Most companies end up using both, for different jobs.
- List the tasks you want AI for and mark each as low, medium or high sensitivity.
- Use a hosted service for low-sensitivity tasks such as drafting and public research.
- For high-sensitivity tasks, use a self-hosted model or design the task so those fields are never sent.
- Respect each user's permissions before any record reaches a model, and cap monthly usage.
- Keep keys in a protected settings store, review the provider's terms yearly, and test switching providers once.
Where ReckonERP fits
The AI features can use a hosted provider or an OpenAI-compatible server, including one you run yourself. Each business can keep its own keys, and a monthly call limit caps usage.
Usage is billed separately from the module subscription. For dedicated or on-premises installations, ask us about keeping AI on your own servers. See integrations for the services that connect.
Conclusion
Hosted and self-hosted AI answer different needs. Hosted gives quality and simplicity; self-hosted gives privacy and control. The sensible answer for most businesses is to use each where it fits and to send a model only what a task requires.
Decide the rules before the first prompt: what may leave, who may ask, and what it may cost. That is far easier than undoing a habit later.
Frequently asked questions
Can I use my own AI server?
Yes, where the operator allows it, an OpenAI-compatible server address can be used.
Does AI see all my records?
No. It works inside the permissions of the person using it and only receives what a task needs.
Who pays for AI usage?
AI and integration usage is billed separately from your module subscription.
Is self-hosted AI always more private?
It keeps prompts on your servers, which is stronger on privacy, but you are then responsible for securing that server.
Can I switch AI providers later?
Yes. Use an OpenAI-compatible interface and keep prompts independent of one provider.
