ACCESS
Role-based access
Granular, role-based permissions decide which teams and users reach which data and AI capabilities — enforced centrally, not per-application.
ENTERPRISE AI
Enterprise-Wide AI at Scale
Granular access control, immutable audit trails, and zero-knowledge architecture — one private AI backbone for organizations with hundreds of users.
Encrypted at rest & in transitData physically yoursIsraeli jurisdictionZero vendor access
[ THE GAP ]
From shadow AI to governed AI
SHADOW AI RISK
Ungoverned today
- Employees use ChatGPT on personal accounts
- No visibility into what data is shared
- Ban policies are universally ignored
- One incident away from regulatory action
WITH SIRIUS-IT
Governed with liracode.dev
- Company-approved AI with full control
- Every prompt logged and auditable
- PII stripped automatically
- Compliance evidence generated automatically
[ GOVERNANCE PILLARS ]
Control that scales to the whole org
IDENTITY
SSO + provisioning
Single sign-on ties every session to your identity provider, so onboarding, off-boarding and group changes flow straight from your existing directory.
EVIDENCE
Immutable audit trails
Every prompt and AI action is logged to a tamper-evident record, giving security and compliance teams a defensible history for review.
ARCHITECTURE
Zero-knowledge design
Inference runs on infrastructure you control and content stays inside your environment — the provider is architected never to read your data.
RESIDENCY
Data stays yours
Data is encrypted at rest and in transit and physically remains under your chosen jurisdiction — no vendor-side copies, no hidden access.
ROLLOUT
One model, every team
The same access and audit model applies whether one division or the whole enterprise is live — expand without re-architecting governance.
[ GOVERNED ROLLOUT ]
Central control, many teams
One SSO + RBAC control plane governs every department over a single private AI backbone — and the same model carries you from a first pilot to org-wide.
CONTROL PLANE
SSO + RBAC governance
Identity, permissions and policy are decided in one place and applied to every team — no per-tool exceptions, no ungoverned access.
Engineering
Code & build assistance, scoped to its own repositories.
Legal
Contract review with full prompt audit and retention rules.
Finance
Analysis on sensitive data that never leaves the perimeter.
Support
Customer-facing AI with PII stripped before inference.
ONE PRIVATE AI BACKBONE — SHARED INFRASTRUCTURE, ISOLATED PER TEAM
[ DEPLOY AT SCALE ]
Pilot
Start with one team on the governed control plane.
Department
Expand to a full division — same access and audit model.
Org-wide
Roll out across the enterprise without re-architecting.
Adding a team is a policy change, not a new system. The control plane, audit trail and private backbone stay the same as you scale from pilot to organization-wide.
[ CAPABILITIES ]
What enterprise governance covers
Role-based
Centralized access control across every team and user
Immutable
Tamper-evident audit trail of every AI action
Zero-knowledge
Architecture where the provider cannot read your data
Your jurisdiction
Data physically yours, encrypted at rest and in transit
These are architectural capabilities of the platform, not customer-usage claims. Scope and rollout are agreed per engagement.
GOVERN AI AT SCALE
Bring AI to the whole org — under your control
Tell us how your teams are structured and where your data must stay. We will scope a governed rollout — from pilot to organization-wide.
[ COMMON QUESTIONS ]
What enterprise buyers evaluate
How do you control access across hundreds of users?
Through granular, role-based access control, so each user and team sees only the data and AI capabilities they are entitled to — enforced centrally rather than per-application.
Can we prove who used AI on what, after the fact?
Yes. Immutable audit trails record AI usage across the organization, giving security and compliance teams a defensible record for internal and external review.
What does zero-knowledge architecture mean for our data?
It means the AI pipeline is designed so the provider cannot read your data: inference runs on infrastructure you control and content stays within your environment, reducing the privacy-incident exposure most large organizations have already experienced.
Do we adopt this per-team or all at once?
Either. All modules plus consulting are available, so you can roll AI out to one division first and expand across the enterprise without changing the underlying access and audit model.