AI Knowledge Base & Company Document Search
Turn maintained company documents into source-linked answers for authorized employees.
What is an AI knowledge base?
An AI knowledge base combines an approved document collection, retrieval and an assistant that explains relevant evidence. It helps locate SOPs, compare product guidance and understand training. It does not make every document current or correct; source ownership, revisions, access rules and citations remain essential.
How does search become an answer?
A retrieval pipeline prepares documents, indexes searchable passages, limits retrieval to the user’s scope and supplies evidence to the model. Answers should identify sources and say when support is missing. Extraction quality, structure and evaluation matter more than simply uploading many files.
- Validate the source file and owner.
- Preserve titles, revisions and permission labels.
- Retrieve only authorized evidence.
- Escalate unsupported or conflicting instructions.
Different questions require different sources
An SOP assistant needs controlled procedures. Product answers need approved specifications. Onboarding needs role-specific training. Live stock and prices should come from permitted operational queries, not old PDFs.
| Question | Source | Review |
|---|---|---|
| How do I receive damaged stock? | Current receiving SOP | Follow escalation rules |
| Which product meets a specification? | Approved technical documents | Verify requirements and terms |
| How much stock is available? | Current ERP query | Confirm location and reservations |
Pilot with deliberate failure cases
Choose a small collection with a reliable owner. Test ambiguous terminology, outdated revisions and requests for restricted material. Measure supported answers, correct citations, refusal behavior and task completion. Expand only after access controls and source updates work.
Prepare files, budget and operations
Bring representative PDFs, spreadsheets and documents, access groups, revision conventions and employee questions. Scanned documents may require extraction cleanup. Planning uses published AI packages; final scope depends on sources, users, infrastructure and integration. Agree how replaced documents leave the index and how administrator access and backups are managed.
Questions before you start
Is RAG model training?
No. RAG retrieves material during a request. Fine-tuning changes model behavior and does not replace a governed source library.
Can it answer without evidence?
Require an unsupported-answer path and escalation for important instructions. Evaluate the behavior instead of assuming it.
Start with one workflow worth improving.
Bring your systems, sample records and operating priorities. We will discuss fit, scope and the next decision.