Straight answers
On-premise vs cloud AI for insurance agencies: which should you pick?
For almost every independent P&C agency, cloud AI is the practical choice. Running AI on-premise means buying GPU servers, licensing the models, and hiring someone to keep them running, which is a data-center project no 7-person agency staffs. The real question is not on-prem versus cloud. It is whether your cloud vendor gives you the security posture on-premise was supposed to buy: scoped access you control and can revoke, encryption at rest and in transit, no training on your data, and full export whenever you want.
| Concern | On-premise | Cloud SaaS, done right |
|---|---|---|
| Upfront cost | GPU servers, model licenses, and an MLOps hire | A subscription, no hardware to buy |
| Who maintains it | Your team patches, monitors, and updates it | The vendor's job, not yours |
| Where data lives | On your own hardware | The vendor's cloud, under contract. Ask about location, encryption, and export |
| Model quality | Limited to what you can license and host | Access to current frontier models the vendor maintains |
| Fit for a small agency | Rare. Needs staff most agencies do not have | The normal path |
The longer version
On-premise AI exists for a reason. Large regulated enterprises sometimes face data-residency mandates that force models to run on hardware they own. Independent P&C agencies almost never carry that mandate. A carrier does not require it, and running your own inference stack trades a monthly subscription for hardware, model licensing, and an ops person you would otherwise spend on producing.
So the decision is really about vendor diligence, not architecture. The questions that matter with any cloud AI vendor: where is my data stored, is it encrypted at rest and in transit, does my data train your models, who on your team can see it, and can I export and delete everything on demand. The standard to expect is AES-256 at rest and TLS 1.2 or higher in transit. If a vendor cannot answer those on paper, that is the red flag, not the fact that they run in the cloud.
Relay is cloud-based and honest about it. It runs inside your own carrier portal sessions using credentials you provision and can revoke with one click, stores credentials in an encrypted vault (AES-256, SOC 2 Type II practices), encrypts client data in transit and at rest, and only touches the data fields a given workflow needs. No bulk extraction, no data mining, and you can export your data. The security page lays out the full posture.
Common questions
Does any insurance carrier require agencies to run AI on-premise?
Not that we have seen. Carriers care how their portal is accessed and whether credentials are protected, not where a vendor's servers sit. If you are unsure, ask your carrier reps directly.
What should I ask a cloud AI vendor about my data?
Where it is stored, whether it is encrypted at rest and in transit, whether your data trains their models, who on their team can see it, and whether you can export and delete everything on demand.
Is Relay on-premise or cloud?
Cloud. Relay runs in your own portal sessions with credentials you provision and can revoke, encrypts data at rest and in transit, and lets you export your data. The security page has the details.
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Part of the Relay straight answers library. Updated 2026-07-11. See how we source content.
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