Use case
Useful answers are split across portals, code, documents, support systems, and work trackers with different access and freshness rules.
AI RAG Search
Useful answers are split across portals, code, documents, support systems, and work trackers with different access and freshness rules.
How it solves it
A source registry and retrieval-oriented UI make source scope, authentication mode, freshness, and indexed fields explicit before an answer is generated.
Architecture
The design separates inputs, orchestration, AI assistance, and human verification. Secrets and environment-specific identifiers belong in runtime configuration, never in this page or source control.
Software stack
Next.js, TypeScript, React, CSS, structured source metadata, local indexing adapters.
Source-controlledTestableObservableLeast privilege
AI and AgenticOps
AI/RAG should rank and summarize approved context, show provenance, and fail closed when a source is unavailable; AgenticOps can schedule refreshes and health checks.
Technical operating model
Ingest
Accept structured inputs and normalize them.
Accept structured inputs and normalize them.
Reason
Retrieve approved context and produce a bounded plan.
Retrieve approved context and produce a bounded plan.
Verify
Apply guardrails, human review, and evidence checks.
Apply guardrails, human review, and evidence checks.
The design distinguishes source coverage from authenticated retrieval so an index is never mistaken for permission to search private systems.