On-Premise AI SIEM for Regulated Organisations
ClaireChains ·
An on-premise AI SIEM runs on servers you control, so logs, alerts and investigations never leave your network. For regulated organisations it makes data residency and audits simpler. Claire Security runs its AI models locally, on-premise or in a hybrid set-up, so you get AI triage without sending telemetry to an outside service.
Why security data is sensitive
A SIEM sees almost everything: user logins, file access, network flows, email metadata and the details of every incident. That makes it one of the most sensitive systems in an organisation. Security logs often contain personal data, trade secrets and evidence that regulators may later ask for.
When that data goes to a vendor’s cloud, you add a processor, a location and often a foreign jurisdiction to every audit. For banks, energy companies, hospitals and public bodies, that is a real cost.
What changes when the AI runs locally
Many AI security tools send alerts and context to an external AI model for analysis. Even if the SIEM itself is on-premise, the most sensitive part, the investigation, then happens somewhere else.
Claire Security uses its own security-trained models. They run on your infrastructure, next to your data. That means:
- Telemetry and investigation details stay inside your network.
- Air-gapped and restricted networks can still use AI triage.
- Inference runs close to the data, which keeps latency low.
- You are not affected when an outside AI service changes its terms, its prices or its availability.
Deployment options
| Option | Where data and AI run | Best for |
|---|---|---|
| On-premise | Everything on your servers, including the AI models | Critical infrastructure, defence, air-gapped networks |
| Hybrid | Raw data and investigation on-premise; selected storage or reporting in the cloud | Organisations that need data control and flexible scale |
The Act 854 guide shows how a hybrid set-up maps to one national law. Our on-premise vs cloud comparison covers the trade-offs in more detail.
What Claire Security does on your servers
- Collects and correlates events from email security, EDR, cloud platforms and network devices.
- Investigates each alert with an agentic reasoning loop: observe, hypothesise, gather evidence, conclude.
- Stores the full reasoning chain with every alert, so decisions can be audited.
- Produces the reports your team and your regulators need.
See how the platform works, or how we measured its results.
Questions to ask any SIEM vendor
- Where do the AI models run, and does any alert data leave our network?
- Can the system run fully disconnected from the internet?
- Who can access our logs, and under which country’s law?
- Can every automated decision be traced and explained to an auditor?
See Claire Security on your own data
Book a demo and we will show you triage, audit trails and reporting in your environment.
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Frequently asked questions
What is an on-premise SIEM?
An on-premise SIEM runs on servers you own or control, in your own data centre or private cloud. Logs, alerts and investigation data stay inside your network instead of being sent to a vendor’s cloud, which simplifies data residency and regulatory audits.
Can an AI SIEM run without sending data to the cloud?
Yes, if the AI models run locally. Claire Security uses security-trained models that run on your infrastructure, so alert triage and investigation do not depend on sending telemetry to an external AI service.
What is a hybrid SIEM deployment?
In a hybrid deployment, sensitive raw data and active investigation stay on-premise, while selected functions such as long-term storage or reporting run in the cloud. It balances data control with scale and cost.