This is for only 1-4 people to use not for everyone in the ORG.

Huntress should consider building a local or customer-controlled AI query server that lets MSPs and customers ask questions across their own security and IT data without sending raw organizational data into a third-party AI platform.

The goal would be a Huntress-managed local AI/RAG appliance that can answer questions such as:

Which endpoints have repeated suspicious PowerShell activity?

Which users had risky sign-ins and also touched sensitive systems?

Which devices are missing EDR, Defender, disk encryption, or recent patching?

Which alerts are likely related to the same incident?

What changed in the environment in the last 24 hours?

Which assets are high risk based on endpoint, identity, vulnerability, and exposure data?

Summarize this incident using only data from this tenant.

This would be valuable for SMB and mid-market customers that want AI-assisted security operations but do not want sensitive endpoint, identity, ticketing, or asset data sent to public AI systems.

Recommended design:

Huntress could provide the image to deploy for a local virtual appliance, lightweight server, or private tenant container that ingests data from Huntress, Microsoft Defender, Microsoft 365, Entra ID, SIEM logs, asset tools, vulnerability scanners, ticketing systems, and firewall/DNS logs. The appliance would build a local searchable security knowledge base using structured storage, vector search, and graph relationships.

The AI model would not need to train on the customer’s data. It should use retrieval-augmented generation, where the model answers questions only from indexed customer data and cites the source records used in the answer. It should keep costs down for huntress.

Important controls:

Raw customer data stays local or tenant-isolated

No default training on customer data

Role-based access control tied to Entra ID or SSO

Full audit logs of every AI query and response

Source citations for every answer

Data retention controls

Prompt injection protection

Sensitive data redaction options

MSP multi-tenant separation

Read-only mode by default

Optional approval workflow before any remediation action

Optional Huntress SOC access only when the customer permits it

This would give Huntress a strong privacy-first AI capability. It would help MSPs and customers query their own security data safely, investigate faster, and reduce analyst workload without turning organizational telemetry into unmanaged AI training data.