Decision framework
Knowledge Assistants: Solution Comparison
Knowledge Assistants: Solution Comparison organizes the decisions that matter for businesses building internal assistants grounded in documents, policies, products, support information, or operational knowledge: the current workflow, ownership, implementation choices, rollout risk, and acceptance evidence.
Working artifact
Knowledge Assistants integration-boundary map
Use the boundary map to show what crosses systems, where it can fail, and how the result will be reconciled.
| Boundary | Information moving | Failure to test |
|---|---|---|
| RAG architecture and vector search | Document ingestion and knowledge indexing | Employees search several repositories for one answer |
| Document parsing and metadata | Retrieval-augmented question answering | Generic AI invents policies or product facts |
| Identity-aware retrieval | Citations and source traceability | Sensitive documents must respect access levels |
Choose Document ingestion and knowledge indexing when
Employees search several repositories for one answer. Confirm who encounters it, where it occurs, and what changed before it appeared. Then distinguish the visible symptom from dependencies such as RAG architecture and vector search.
- Employees search several repositories for one answer
- RAG architecture and vector search
- Document parsing and metadata
Choose Retrieval-augmented question answering when
For Custom AI Assistants & Knowledge Systems, confirm account ownership, current exports or backups, recovery options, and recent changes before touching production. Preserve exact errors and timestamps that may disappear after a restart or update.
- Generic AI invents policies or product facts
- Sensitive documents must respect access levels
- Identity-aware retrieval
Compare the tradeoffs
Frame the first scope around document ingestion and knowledge indexing and one observable acceptance journey. Treat retrieval-augmented question answering as a later phase unless the evidence shows it is a true dependency.
- Time to verified result
- Data and access risk
- Maintenance responsibility
- Ability to reverse course
A low-risk decision sequence
Repair fits when the core remains sound. Extension fits when the boundary around RAG architecture and vector search is understood. Replacement fits when ownership, architecture, or operating risk prevents a responsible change.
- Inventory
- Focused test
- Decision record
- Scoped implementation