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What is Membria EE and who it serves
Membria EE (Enterprise Edition) is an on-premise AI reasoning platform for organizations that operate under strict compliance, data residency, and security requirements. It preserves institutional memory by turning decisions, assumptions, and rationale into durable, auditable records.
Membria EE is not a chatbot and not a document management system. It is a reasoning and decision infrastructure that integrates with existing enterprise tools rather than replacing them.
Why enterprises need institutional memory
Enterprises already generate critical decisions across chats, tickets, documents, internal copilots, and analytics systems. What is usually missing is a persistent layer that preserves why decisions were made, not just what happened.
Relying on long context windows does not solve this problem. Retrieval quality degrades in the middle of long contexts, and costs rise with every query. Traditional vector RAG systems help search, but they do not capture causality, versioning, or decision lineage.
Membria EE addresses this by modeling decisions as structured events inside a temporal graph so that reasoning, causality, and outcomes remain traceable over time.
Who it is for
Membria EE is built for organizations where:
- data is regulated or sensitive by default,
- AI usage must be explainable, reviewable, and auditable,
- decisions must remain traceable years after they are made.
Typical users include:
- banks and financial institutions,
- telecommunications providers,
- regulated enterprises running internal AI initiatives,
- organizations with strict governance, risk, or model-risk management requirements.
Core architectural approach
Membria EE captures institutional memory with a temporal knowledge graph:
- Event-centric memory: decisions are stored as events with who, what, when, and why.
- Causality and lineage: decisions link to inputs, alternatives, and outcomes.
- Versioning over time: superseded decisions remain auditable, not overwritten.
- GraphRAG retrieval: queries traverse graph context instead of raw text similarity.
This preserves the reasoning chain, not just the final artifact.
What you get
Dedicated deployment options
- Fully isolated on-premise or private-cloud deployments
- No shared inference or shared memory by default
- Infrastructure aligned with enterprise security and IT policies
Private knowledge domains
- Organization-scoped reasoning graphs
- Explicit separation between teams, domains, and projects
- No cross-tenant or cross-organization leakage
Private Council and cache controls
- Controlled escalation to approved internal or external models
- Enterprise-owned knowledge cache
- Full visibility into when, why, and how escalation occurs
Enterprise governance and auditability
- Immutable decision records
- Clear causality between inputs, reasoning, and outcomes
- Support for audits, compliance reviews, and post-incident analysis
What Membria EE does not do
- It does not replace existing chat tools, ticketing systems, or document platforms.
- It does not train global or shared models on enterprise data.
- It does not introduce autonomous decision-making without human oversight.
Membria EE operates as a governed reasoning layer, not as an autonomous agent.
Positioning summary
Membria EE enables enterprises to use AI without losing control over reasoning, accountability, or institutional memory.
It turns fragmented AI usage into a coherent, auditable decision system. 
