Enterprise security at every layer
Security, compliance, and auditability are foundational to Luceris, not afterthoughts. Every layer of the platform is designed to protect your data, govern AI behavior, and maintain the trust your enterprise demands.
Core Security Principle
Your operational data never trains AI foundation models. Luceris uses AI for inference and reasoning within your governed environment. Your data stays yours, scoped to your tenant, your workspaces, and your approval chains.
Security architecture
Six pillars that protect your data and operations across every layer of the platform.
Data Isolation
Every customer's data is scoped to their organization on every read and write, and that scoping is enforced in code review and mechanically in CI rather than left to convention. Within each tenant, Workspaces provide an additional layer of internal segmentation, so teams and agents only reach what they should. Agent state is scoped per workspace and deleted on teardown.
- Organization-scoped isolation on every data-access path, enforced in CI
- Every request bound to a single organization by a verified token claim
- Workspace-level internal segmentation for teams and agents
- Agent state scoped per workspace and deleted on teardown
Encryption & Access Control
All data is encrypted in transit using TLS 1.2+, and encrypted at rest by the managed data services we run on. Access is governed by role-based access control (RBAC) that maps to your organizational structure. Your source-system credentials are held in a dedicated secrets manager and referenced only by identifier, never inlined into application code or configuration.
- TLS 1.2+ encryption for all data in transit, with no unencrypted protocols
- Encryption at rest across all managed data services
- Role-based access control (RBAC) mapped to your org structure
- Integration credentials isolated in a secrets manager, referenced by identifier
AI Model Governance
Your operational data never trains foundation models. Before any prompt reaches a model provider, personal details in it are replaced with stable tokens, and those tokens are only resolved back for authorized users in your own browser. Agents query your data through read-only, privacy-coarsened views, and every action an agent proposes must pass through human-gated approval before execution.
- Operational data is never used to train or fine-tune any model
- Personal details tokenized before prompts reach a model provider
- Zero data retention enforced on our OpenAI traffic
- Agents read through read-only, privacy-coarsened views only
- File processing runs in isolated sandboxes with all outbound network denied
- Agents cannot take autonomous action without approval
Explainability & Transparency
Every insight an agent surfaces includes the contributing entities and source systems that informed it. Decision context is fully inspectable, so your teams can understand not just what was recommended, but why.
- Contributing entities visible for every insight
- Source systems identifiable for each data point
- Decision context fully inspectable before approval
- Confidence scoring with supporting evidence
Compliance Alignment
Luceris is SOC 2 certified. Every action and decision is traceable, events are logged in a structured form you can report against, and data-governance rules are enforced in the platform rather than documented and hoped for.
- SOC 2 certified
- Full audit traceability for every action and decision
- Structured event logging for compliance reporting
- Data-governance rules enforced in the platform, not by policy alone
Operational Resilience
The platform is built on fault-tolerant infrastructure with data versioning and recovery capabilities. Structured event logging ensures that every state change is tracked and recoverable.
- Fault-tolerant infrastructure with redundancy
- Data versioning and point-in-time recovery
- Structured event logging for all operations
- Graceful degradation under failure conditions
AI governance model
Luceris agents are governed by design. Every action is proposed, reviewed, and approved before it touches your systems of record.
Explicit approval required
Every write action requires human authorization before execution. Agents surface recommendations and evidence, but only authorized stakeholders can approve changes that flow back to your systems of record.
Change previews
Before any action is approved, stakeholders see exactly what will change: which entities are impacted, what data will be written, and to which systems. No hidden side effects.
Full audit trail
Every approval logs the authorizing user, timestamp, complete action context, and outcome. This creates a compliance-ready record of every decision made through the platform.
Scoped boundaries
Agents operate strictly within their assigned Workspace boundaries. They cannot access data outside their scope, override defined policies, or escalate their own permissions.
Version history
All changes are versioned with conflict detection to prevent silent overwrites. If two actions target the same entity, the system flags the conflict for human resolution.
Layered trust model
Intelligence is only introduced after data is connected, normalized, and governed. Each layer of the platform builds on the security guarantees of the layers below it.
How your data is handled
Transparency into how data moves through the Luceris platform.
Data ingestion
Data is read from your systems of record through managed integrations. We normalize formats, reconcile entities, and structure everything into your Entity Graph. Your source systems remain authoritative.
Data storage
Your Entity Graph is stored in a tenant-isolated, encrypted environment. Data is versioned with temporal tracking so you can inspect changes over time. No customer data is shared across tenants.
AI processing
Agents analyze your Entity Graph within scoped Workspace boundaries, reading through read-only views that coarsen sensitive columns. Personal details are tokenized before prompts reach a model provider. Your data is used for reasoning only and never contributes to model training.
Write-back
Approved actions are synchronized back to your systems of record through the same managed integrations used for ingestion. Every write-back is logged with a full audit trail including the approving user and decision context.
Questions about security?
Our team is available to discuss your specific security requirements, compliance needs, and data governance policies.