TenantSage™ is the Governance-First RAG architecture designed to support legal defensibility — embedding Identity Scoping, Role Hierarchies, and Legal Holds directly into the database engine.
Enterprises are rushing to adopt Generative AI, but face a critical blockade. Standard RAG systems are designed for retrieval speed — not legal safety.
An AI summarising a "Global Policy" might accidentally surface a confidential "Local HR Issue" to the wrong staff member. Standard RAG denormalises permissions — creating invisible data exposure at query time.
AI models cannot naturally understand Legal Holds. They will happily summarise a lawsuit document that should be frozen — creating liability via hallucination that standard architectures cannot prevent.
The Market Gap: Enterprises need AI that is not just smart, but designed to support legal defensibility. Bolting security onto the application layer is too late. The governance must live inside the retrieval engine itself.
TenantSage inverts the standard model. Instead of bolting security onto the application layer after retrieval, we embed strict governance directly into the database engine — before any prompt is ever constructed.
The result is an AI system architected to significantly reduce the risk of protected data exposure at the retrieval layer — by design, not by policy.
TenantSage treats the AI as an untrusted entity. If a document is expired, on legal hold, or outside a user's strict role — the system is designed to render it absent from the retrieval path before the prompt is ever constructed.
Our IP strategy targets not just the software — but the Method. Competitors can build RAG and they can build Permissions. TenantSage is designed so they must exist as a single, indivisible atomic unit — and that architecture is what we have filed protection over.
Our license restricts "decoupling" governance from retrieval. This creates a structural architectural dependency — binding customers to our standard and supporting long-term IP retention across every deployment.
Semantic relevance evaluated in the same operation as governance — never before, never after.
Parent-source inheritance means role access cascades from the schema itself, not application code.
Time-Travel Prevention is designed so expired documents are structurally excluded — with no standard retrieval path available once a document is outside its effective window.
Legal Quarantine logic operates at the retrieval layer, making compliance an architectural property.
Precedence rules are resolved in-engine. No post-retrieval patching. No workaround surface area.
We do not build systems. We evaluate them — against a defined governance standard. The Governance Architecture Review is the only engagement we offer without a prior licensing relationship.
An independent evaluation of how your enterprise AI retrieval layer handles governance — delivered as a written report your board, legal counsel, and engineering team can all use.
The review is conducted via architecture documentation and structured technical discussion. No access to live systems or production data is required.
All engagements are conducted under mutual NDA. Execute online →
Fixed fee. Not volume-based. Not hourly. Quoted on request following scope confirmation.
Written report delivered to nominated stakeholders. One follow-up session included.
We license the Canonical SQL Schema and Governance-as-Code artifacts. Enterprises and SIs avoid 6+ months of high-risk R&D and inherit a production-validated and architecturally reviewed foundation.
A governance benchmark for enterprise AI systems enforcing retrieval-layer compliance. Signals that a deployment is architected to respect Legal Holds, Role Hierarchies, and Time-Travel Prevention — supporting auditor evaluation frameworks.
Our license contractually restricts decoupling governance from retrieval. This binds customers to our standard — creating a structural dependency with every deployment at scale.
TenantSage is not a roadmap. It is a production-ready governance infrastructure with an executed IP filing strategy and a structurally engineered approach to the enterprise AI governance gap.
Full Governance-as-Code artifacts are audited and production-ready. The canonical schema has been validated against enterprise-scale retrieval workloads.
Trademark Filed · Authorship Recorded
IP strategy executed via Statement of Authorship and formal Trademark filing for the "Real-Time Inheritance Retrieval Path™" brand — defensible by filing record pending full registration.
Legal Quarantine logic is engineered to exclude holds, role violations, and expired documents from the retrieval path at the architecture layer — not by policy, but by structural design.
Start with a Governance Architecture Review — the only engagement we offer publicly. Or request a confidential investor briefing.