Knowledge · International teams
AI knowledge base preparation
Prepare a source collection that an assistant can search, cite and keep up to date.
Understand the service
What this means in practice
Knowledge base preparation is the work that comes before a useful company assistant: finding authoritative documents, removing confusing duplicates, identifying access rules and assigning ownership. Adding more files is not automatically an improvement. A smaller, maintained collection can be easier to evaluate than a large folder of conflicting material.
Temrik can assess one information set before retrieval is configured. The work should retain document structure, version and source identity, then make gaps visible. This is distinct from the answering layer: first establish whether the source material itself is suitable for the questions staff need to ask.
- Microsoft: retrieval-augmented generation Retrieval supplies context; source preparation and evaluation matter.
- Microsoft: document-level access control Document permissions and their synchronisation require explicit design.
A practical workflow example
A support team has several versions of a service guide spread across shared folders. The proposed preparation work identifies the approved version, archives obsolete copies from the retrieval scope and records an owner. A test question about an outdated service reveals whether old material can still appear in results.
Proposed engagement
How we would approach the work
Inventory and reconcile
List source locations, owners, duplicates, versions and access groups. Resolve conflicting guidance with the content owner instead of asking AI to choose.
Prepare usable content
Check text extraction, headings, tables and source references. Define how documents are divided for retrieval without losing important context.
Plan maintenance
Specify refresh, correction and removal processes. Keep representative questions to test whether changes improve the collection.
Deliverables to agree in the scope
- A source inventory and content-quality findings.
- A proposed preparation and metadata specification.
- An ownership, refresh and removal plan.
Access, sample information and reviewer availability affect the plan. Any implementation, provider costs, support arrangements and acceptance criteria are agreed before work begins.
Limits worth understanding
- Content preparation cannot create authoritative answers where the business has no agreed policy.
- Scans, complex tables and fragmented records may need manual correction before retrieval is useful.
Questions to bring to the first conversation
- Who can declare a document authoritative?
- Which questions have no approved answer yet?
- How will obsolete material be removed?
International teams
Scope the work for your operating context.
For a global knowledge base, label regional applicability and document language before combining collections. Keep the source owner for each policy and test whether an answer selects the correct regional version rather than the most frequently repeated wording.
A starting reference for your review: NIST: AI Risk Management Framework. Local obligations and deployment settings need to be assessed for the actual use case.
A focused next step
Work with Temrik.
Tell us about the workflow you want to improve and the outcome you need. We can review the context and discuss a focused assessment. Scope and price are agreed before paid work begins.