Private AI vs ChatGPT Enterprise: what to evaluate
A hosted enterprise assistant and a privately deployed AI platform solve overlapping problems in different ways. This page sets out what to evaluate so you can choose for your own situation.
Two approaches
A hosted enterprise assistant is a service run by a vendor and used by your people. A privately deployed platform runs inside infrastructure you control and is connected to your own knowledge.
Neither is better in every case. The right choice depends on your data, your rules and your teams.
What to evaluate
Use the same seven questions with every vendor, including us.
| Question | Private deployment (MotionPexels Enterprise AI) | ChatGPT Enterprise |
|---|---|---|
| Where does your data live? | In your own cloud, VPC or on-premises, as you choose. | Confirm against the vendor’s current documentation. |
| How are permissions applied? | Answers are filtered by each user’s existing permissions. | Confirm against the vendor’s current documentation. |
| Do answers cite sources? | Citations on every response, from approved knowledge. | Confirm against the vendor’s current documentation. |
| What is logged for audit? | Every query, action and approval is logged and traceable. | Confirm against the vendor’s current documentation. |
| Which systems does it connect to? | Common integrations include Slack, Microsoft Teams, Salesforce, Jira, Confluence, Zendesk, Snowflake, SAP, Google Drive and SharePoint. | Confirm against the vendor’s current documentation. |
| Can you choose the model? | Yes. Commercial or open models, hosted where you require. | Confirm against the vendor’s current documentation. |
| How is it deployed? | Your cloud, your VPC or fully on-premises. | Confirm against the vendor’s current documentation. |
Where a private deployment fits
- You need data to stay inside your own infrastructure or country
- You need answers filtered by your existing source-system permissions
- You need a full audit trail of queries and actions
- You want to choose, or change, the model behind the platform
- You want agents that run governed workflows with approval gates
How to run a fair evaluation
- Write down your requirements for data location, permissions and audit before you see any demo
- Pick ten real questions from your teams, including some that touch restricted documents
- Run the same questions through each option and record the answers and their sources
- Check that a user without access to a document gets nothing drawn from it
- Ask each vendor to show you the audit trail for the test
- Compare the total effort to deploy, govern and maintain each option
Effort and cost to consider
Compare more than the license. Include the effort to connect your sources, to configure permissions, to govern content over time and to answer your security team’s questions.
A cheaper option that takes months to approve may cost more than a pricier one that clears review quickly. We do not quote prices on this page, and you should ask every vendor for a scoped estimate against your own requirements.
Where a hosted assistant may be enough
If your data is low-sensitivity, you do not need private deployment and you mainly want a general-purpose assistant for individuals, a hosted service can be simpler to adopt.
The cost of that simplicity is less control over where data lives and how the system is governed. Check that against your own policies.
Frequently asked questions
Is a private LLM better than ChatGPT Enterprise?
It depends on your requirements. A private deployment gives you control over where data lives, which models you use and how everything is logged. A hosted assistant can be simpler to adopt.
Can I use both?
Yes. Some organizations use a general-purpose assistant for low-sensitivity tasks and a private platform for work that touches confidential data.
What should I ask any vendor about data?
Where data is stored, whether it is used to train models, how long it is retained, who can access it and how that is logged.
How do I evaluate permissions?
Test it. Connect a restricted document and check that a user without access gets no answer drawn from it.
Compare it on your own data
Book a 30-minute demo and we will run the same questions through the platform with your documents.