DELIVERY REVIEW / Enterprise knowledge assistant
Enterprise RAG knowledge base & AI assistant case
This project addresses internal document searches and repeated questions. It first defines answerable knowledge, then adds retrieval, source display and human review. Internal use helps assess answer quality before broader adoption.
Starting point
Documents were growing while teams repeatedly answered similar questions. The project first clarified which materials could support answers, who maintained them and which questions required human handling.
First-phase delivery scope
- Answerable scope and document organization
- Knowledge retrieval, citations and repeated questions
- Internal use, result review and ongoing improvement
Acceptance focus
These checks summarize the public project review to explain expected system behavior. Actual acceptance follows the confirmed project documentation.
- Answers have sources
Check whether answers reference supporting documents instead of treating generated text as fact.
- Scope stays controlled
Test unanswered and out-of-scope questions to ensure human escalation remains available.
- Results can be reviewed
Record failures and feedback to improve documents and retrieval over time.
What changed in the business?
Internal use first validated document lookup and repeated-response workflows before considering expansion. Public materials provide no standardized accuracy or time-saving figures; demonstrations do not replace ongoing evaluation.
Scope and limitations
Knowledge assistants cannot guarantee every answer. Document quality, permissions and evaluation need ongoing maintenance. Sending external messages or changing business data requires separate authorization and review design.
Content source: Jianxu Digital project reviews . Confidentiality agreements prevent publication of production URLs, accounts, client names and raw business data.