Is anyone building / using AI Agents for Veeam?

Minor correction:

Veeam officially released something called Agent Commander (announced in February 2026). This focuses on detecting risks created by AI agents, protecting against them, and even undoing AI mistakes (rollback/restore). But it's more about "managing / protecting AI agents" rather than an agent that automates Veeam backup operations itself.

Agent Commander is a part of the Securiti AI ecosystem which Veeam plans to work with, but details / integration are to be announced.

Stay tuned for more announcements on Agent Commander and Veeam Backup & Replication.

I haven’te heard anything definitive as of yet ​@tarik.yenisey , aside from what ​@ddomask shared above.

Only AI I use is Veeam Intelligence lately as it works extremely well.  I do use other AI tools but not specifically for anything other than maybe helping develop say PowerShell scripts for tasks, etc.

AI solution providers say they can build something for Veeam. But right now, there aren't any off-the-shelf or ready examples available, so I'm researching this myself. Regarding Veeam Intelligence, the fact that data can be exported/sent externally is a concern from a security standpoint, so we're not warming up to it at the moment. We handle a significant amount of customer data, and since the data responsibility and compliance obligations fall on us/me, we need to be very cautious.

Highly agree there as I use Veeam Intelligence mainly in my homelab vs work.  We are similar in we need to be cautious of customer data.  It will be interesting if someone builds a solution for Veeam or maybe Veeam will even build one themselves, you never know. 😉

Thank you for this valuable discussion. I'm currently in talks with a few companies. I'll keep you all updated on any developments.

Great discussion. This is something I have been thinking about and actively working on.

The Veeam REST API surface is actually quite capable for agentic use: job status, repository health, restore operations, alert queries, session history. The primitives are all there. What is missing is an orchestration layer that can reason about them in natural language and take action. Personally I find the natural language interaction side of this genuinely enjoyable to work on. There is something satisfying about bridging a complex API surface and being able to just ask it what is wrong.

Tarik's point about Veeam Intelligence and external data is the exact right concern for anyone running managed services or handling regulated customer data. The architecture that solves that is an on prem LLM fronting the Veeam REST API, with the model calling defined function tools rather than freeform querying. No customer data leaves the environment, and you keep full control over what actions the agent is permitted to take autonomously versus what requires human confirmation.

Agent Commander is worth noting separately. It is focused on protecting against what AI agents do to your data: detecting drift, enabling rollback, containing the blast radius of an autonomous process gone wrong. That is a genuinely important problem as agentic workloads become more common in production environments, and it would not surprise me to see Veeam address both ends of this over time.

Nothing production ready to share yet but happy to compare notes as this develops. The demand is clearly there.