RAG Knowledge Architecture
Give your teams AI-assisted access to knowledge they can actually trust
AI answers in regulated environments must cite their source. This service enforces that by design.
Free Download
EU Data Residency Green List: Irish SME Edition
AI tools assessed against three criteria: EU data residency guarantee, no training on customer data, and a signed DPA. Use it before selecting tools for any governed AI workflow.
The Problem
Why this matters
AI tools produce unreliable outputs when the source knowledge is fragmented. In regulated environments, an answer that cannot be traced to an authoritative source document is not useful. It is a risk. When staff rely on AI-assisted outputs for compliance decisions, client advice, or operational procedures, every output needs to be verifiable.
Most RAG implementations are built by developers focused on the retrieval mechanics. What most lack is the governance layer: a defined trust hierarchy that resolves conflicting sources, a confidence threshold that stops the system guessing when it does not know, and a currency governance process that keeps the knowledge base current after the initial build.
Every AI output in a regulated environment must be traceable to a source document and section. Below a defined retrieval confidence threshold, the system should decline to answer and route to a human. Guessing confidently is substantially worse than saying it cannot find the answer in a compliance context.
What Is Included
Knowledge discovery, architecture design, build, and governance, delivered as a complete system:
- Knowledge source audit: what exists, where it lives, current quality, currency, and ownership
- Trust hierarchy definition: which sources are authoritative, which are secondary, which should not be used
- Gap identification: knowledge that should exist but does not, before the build starts
- Retrieval architecture design: chunking strategy, indexing approach, relevance controls, confidence thresholds
- Build and testing: system implemented and validated against real queries from the knowledge domain
- Currency governance process: who updates what, when, and how the system stays accurate over time
Every output from the system is traceable to a source document. If it cannot be traced, the system says so rather than guessing.
Deliverables
What you receive
- Knowledge Source Register: every source assessed for currency, authority, accessibility, and ownership
- Trust hierarchy document: primary, secondary, and excluded sources defined and agreed
- Knowledge gap register: gaps identified before build, with recommended remediation
- Retrieval architecture specification: chunking, indexing, confidence thresholds, scope refusal logic
- Implemented RAG system, tested and validated
- Currency governance process and operating guide
- Handover documentation
Enterprise Ireland
If your organisation is Enterprise Ireland-supported, you may be able to recover up to 80% of project costs via the Digital Discovery Grant. Book a discovery call and we will confirm your eligibility as part of the conversation.
Scope and boundaries
What we are
We have received comprehensive training and are knowledgeable across the full scope of EU AI Act obligations: risk classification, provider and deployer requirements, governance architecture, post-market monitoring, and fundamental rights assessments. Clear Gate Systems applies this knowledge to design and implement technical governance architecture for clients.
What we are not
Clear Gate Systems does not provide legal advice, legal interpretation of specific obligations, or regulatory representation. Where your organisation requires a formal legal opinion, on the classification of a specific system, on contractual obligations with an AI vendor, or on regulatory exposure, a qualified solicitor or barrister must be engaged. Our role is to build the technical governance infrastructure that qualified legal counsel can stand behind.
Want to discuss your requirements?
Book a discovery call to discuss your requirements. We will recommend an approach based on what you are actually trying to solve.