Data and sources
Customer data, repositories, connected systems, and retrieval scope remain subject to enterprise controls and policy-led access rules.
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Book a discovery sessionSecurity & Trust
Trust starts with what the platform protects.
T-Flux is built for sensitive enterprise operating environments. The security architecture assumes regulated data, controlled users, governed sources, model discipline, and a requirement for audit-ready evidence across the full AI lifecycle.
Security architectureLayered control for private enterprise AI.
Data sovereignty
Governed inference
Audit-ready evidence
What T-Flux protects
Security is part of the operating model.
Every part of the AI lifecycle is considered: from the sources and models an organisation trusts to the people, records and controls that make outcomes reviewable.
Models and orchestration
Approved model endpoints, orchestration policies, and inference paths are governed rather than left to uncontrolled runtime behavior.
Users and privileges
Identity, role, privilege, and administrative access are part of the security architecture, not an afterthought.
Records and workflows
Prompts, responses, execution records, jobs, and operational events can be captured as controlled evidence.
Audit artefacts
Evidence packs, governance reports, citations, and policy events support oversight and review.
Tenant separation
Hosted or customer-controlled deployment is structured around tenant isolation and enterprise boundary control.
Control model
Security architecture layers.
The security posture is best understood as layered control: deployment, identity, data governance, inference control, and evidence-led oversight.
Deployment layer
Supports Solveworx-hosted, private cloud, and on-prem deployment models aligned to data-locality and infrastructure control needs.
Identity and access layer
MFA, SSO integration, RBAC / ABAC policies, and privileged administrative restriction.
Governed data layer
ACL-aware retrieval, source permissions, trust labels, retention logic, masking, and controlled sync boundaries.
Inference and response layer
Model registration control, orchestrated generation, guardrails, refusal thresholds, and policy-aware response handling.
Audit and observability layer
Traceable logs, operational dashboards, evidence packages, and export-ready governance artefacts.
Private by design
Make enterprise AI secure, governed and accountable.
Explore how T-Flux can fit your data perimeter, operating model and oversight requirements.
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