The platform layer for secure,sovereign AI operations.
Lorenz provides jurisdiction routing, advanced RAG governance, scoped execution, and full audit trails so AI operations remain powerful without becoming ungovernable.
Architecture layers
Five integrated planes govern every workload that passes through Lorenz.
Jurisdiction Routing
Every workload can be assigned to a local-only, in-country, or approved external lane based on data class and regulatory scope.
Hybrid RAG Governance
Retrieval combines semantic, lexical, and operational memory layers while the RAG Governor handles claims, conflicts, and memory coherence.
AEGIS Guardrails
Prompts, commands, and risky parameters are screened for destructive intent, prompt injection markers, and dangerous execution patterns.
Scoped Execution
Skills and tools run under explicit policy, human confirmation, workspace boundaries, and action logging instead of broad ambient trust.
Audit And Recovery
Action Journal, undo snapshots, heartbeat, and version traceability make incidents visible and reversible.
Core positioning
Three pillars that define how Lorenz behaves as a governed platform instead of a generic agent shell.
Sovereign By Territory
Lorenz can run where the customer needs the data to stay: on-premises, in-country, in-region, or inside a private perimeter aligned with local law.
Fortress By Architecture
Security is not a plugin. Sensitive routing, AEGIS controls, scoped execution, audit trails, and rollback are built into the operating model.
Agents Without Sprawl
Lorenz is designed for governed execution, advanced RAG, and multi-tenant control instead of ad hoc tool sprawl and silent data egress.
Advanced RAG with real governance
Lorenz does not treat retrieval as a black box: memory, OCR, and ranking stay under policy and observability.
- Hybrid retrieval combines semantic search, lexical search, and hot SQLite L0 lookups so Lorenz can answer quickly without losing factual grounding.
- The RAG Governor manages canonical claims, contradiction handling, and memory coherence instead of letting every retrieval become permanent truth.
- Conflict monitoring and heartbeat give the retrieval layer operational visibility instead of treating it as a black box inside the assistant.
- OCR is policy-routed, so document extraction follows the security posture instead of bypassing it through hidden third-party egress.
Multi-tenant isolation by construction
Isolation does not live in one control only: it is enforced across identity, queries, workspaces, runtime, and recovery.
- JWT tenant claim checks reject token and tenant mismatches before the request can cross a workspace boundary.
- Request-scoped tenant context and tenant-bound data access reduce accidental scope mixing across services and queries.
- Tenant-dedicated local workspaces and strict path validation reduce cross-tenant file access and path traversal risk.
- Tenant-wide heartbeat and per-user runtime visibility make it easier to detect stale, missing, or unexpected agents.
- Lorenz favors explicit errors and remediation paths over silent fallbacks that hide integrity violations.
Controlled task execution
Lorenz is built to act for real, but never under ambient trust: skills, tools, and side effects stay inside explicit boundaries.
- High-risk operations can require human confirmation instead of relying on model confidence alone.
- Skills and tools execute inside explicit scope, allowlist, and policy boundaries rather than under broad ambient trust.
- Local execution scope validation prevents commands from wandering outside the permitted workspace and tmp boundaries.
- Workspace snapshots plus undo make destructive mistakes reversible when a controlled rollback path exists.
- Execution history stays visible to operators, so automation remains accountable rather than mysterious.
Build on a governed platform
Start deploying AI operations with built-in sovereignty, security, and auditability.