RAG and knowledge systems
Connect questions to permissioned sources with citations, access rules and honest no-answer behaviour.
Relevant answers cite the approved source and stop when support is weak.
Staff search repeatedly, but source freshness and access rights are inconsistent.
The source set is permissioned, owned and maintained.
A source inventory, retrieval architecture, evaluation set and freshness plan.
Access is enforced before retrieval, not only after an answer is generated.
- Capture the event
Staff search repeatedly, but source freshness and access rights are inconsistent.
- Resolve context
Question → permission filter → retrieval → grounded answer → citation → feedback
- Apply the rule
Access is enforced before retrieval, not only after an answer is generated.
- Human control
A named person reviews ambiguity or consequential action for rag and knowledge systems.
- Verify the effect
Read back the important state, record exceptions and confirm the next owner.
The straightforward path is only half the design.
Ownership should remain clear when input is ambiguous, a provider only partly succeeds or a person needs to take over.
Open controls and recovery detail
Human controls
- 01Access is enforced before retrieval, not only after an answer is generated.
- 02Name the person who can approve, pause or reverse the consequential step.
Failure modes
- 01A restricted document is retrieved for a user who should not see it.
- 02Unknown provider outcomes are retried without checking whether the first action succeeded.
Example architecture
An implementation pattern for RAG and knowledge systems, with the controls, failure paths and delivery boundary made visible.
- Capture the event
Staff search repeatedly, but source freshness and access rights are inconsistent.
- Resolve context
Question → permission filter → retrieval → grounded answer → citation → feedback
- Apply the rule
Access is enforced before retrieval, not only after an answer is generated.
- Human control
A named person reviews ambiguity or consequential action for rag and knowledge systems.
- Verify the effect
Read back the important state, record exceptions and confirm the next owner.
Open implementation considerations
Assumptions
- The source set is permissioned, owned and maintained.
- The current process and authority boundary can be documented before build work begins.
Platform and integration detail
- Question → permission filter → retrieval → grounded answer → citation → feedback
Failure modes
- A restricted document is retrieved for a user who should not see it.
- A provider action succeeds but the local workflow does not record the new state.
Human controls
- A named owner reviews ambiguous input.
- Irreversible or customer-facing effects require the agreed approval rule.
What Keystone would deliver
- A source inventory, retrieval architecture, evaluation set and freshness plan.
- Acceptance cases, exception handling and handover notes for the agreed scope.
Limitations
- There is no authoritative source or access model.
- Access is enforced before retrieval, not only after an answer is generated.
Sources behind the explanation
Current platform documentation and implementation principles sit here, separate from Keystone delivery evidence.
Controlled workflow design principles
Consequential workflows need explicit ownership, stable event identity, visible exception states and a defined human authority for ambiguous or irreversible actions.
Open source and scope
- Source
- Keystone engineering policy derived from implementation and acceptance-test practice
- Boundary
- These principles guide design. They do not prove a particular workflow has been deployed or will produce a commercial result.
- Freshness
- stable
What affects the scope?
What would Keystone deliver for RAG and knowledge systems?
A source inventory, retrieval architecture, evaluation set and freshness plan. The exact boundary is agreed after the current process, access and acceptance cases are understood.
When is RAG and knowledge systems not the right next step?
There is no authoritative source or access model.
Does this page describe a customer deployment?
Only evidence labelled Production implementation can imply a real production deployment. Reference architecture, best practice and official documentation explain the approach without making that claim.
Show us the process that keeps getting stuck.
The request keeps this page and its intent attached. A person reviews the context before any customer-facing follow-up.
Discuss your workflow