Encrypted data layer
Data is encrypted in transit and at rest, with keys held in the customer's own key management system where required.
Security
Trust is not a feature. Access control, encryption, auditability and residency are part of the platform's architecture, and part of how each deployment is configured.
Controls
Controls are applied in the deployment, not described in a document and left to the customer to implement.
Data is encrypted in transit and at rest, with keys held in the customer's own key management system where required.
Access boundaries follow your identity provider and role model, for people and for the agents acting on their behalf.
Requests, retrievals, model choices, agent steps and approvals are recorded so a decision can be reconstructed later.
Platform health, connected sources and workflow activity are monitored, with alerting into your operations process.
Outbound connections only where possible, scoped credentials, and explicit allow-lists for every integration.
Data stays in the region you choose, and retention periods follow your policy rather than a vendor default.
Operating principles
The difficult cases are the ones that decide whether an AI system is trusted: an ambiguous request, an unexpected tool call, a model that has drifted.
A new integration, agent or user starts with the minimum scope needed and is widened deliberately.
Irreversible, financial or customer-facing actions require a named approver with the context to decide.
Which models may process which data is a policy decision, reviewed when models or regulations change.
Retrieval returns the passages needed for the task, not whole repositories, and logs record what was read.
Certification status. We do not claim certifications on this website. Current attestations and security documentation are provided during procurement under NDA. Ask for the security pack when you contact us.
Get a demo
We will walk through the deployment model, access boundaries and audit trail against your own requirements.