Explore how enterprise AI projects address role-based access, data isolation, action logs and API security in line with your company’s requirements.
Let’s talk about your AI projectWho may access each source? Which actions need approval? Where is data processed? We address these questions at the start, making security requirements part of the architecture and acceptance criteria.
A user who cannot open a document should not be able to obtain its contents through an AI response. Identity, roles and source permissions are considered across retrieval, generation and tool use.
Access testing includes attempts to reach unauthorised information.
We review where data originates, where it is stored, the context sent to a model and retention needs. Hosting, isolation and provider choices follow the organisation’s requirements; any compliance claim needs a specific assessment.
Data processing and deletion responsibilities are defined for each project.
Logging and monitoring are designed around tool calls, outcomes and approvals while avoiding unnecessary retention of sensitive content. API security, input checks and malicious-content scenarios are included in the testing scope.
Security controls need ongoing ownership beyond the initial release.
Access, permissions and auditability are designed from the start. What a user can retrieve through AI should stay within their existing authorization.
Our approach to securityTell us about your processes, data and challenges. Together, we can identify a practical first use case.