AI & Automation
AI Knowledge Base Development
Internal documentation grows faster than anyone can keep a table of contents for, and keyword search often fails when someone doesn't use the exact terms the doc was written with. An AI-powered knowledge base search understands the intent behind a question, not just literal keyword matches, and can synthesize an answer from multiple documents at once.
This is built as a retrieval layer over your existing documentation — wikis, PDFs, help articles — rather than requiring content to be rewritten or migrated to a new platform.
Problems This Solves
- arrow_rightInternal documentation that's grown too large for keyword search to find the right answer reliably
- arrow_rightStaff asking colleagues questions that are actually already answered somewhere in existing docs
- arrow_rightContent spread across multiple tools (wiki, shared drive, help desk) with no unified search
- arrow_rightOnboarding new staff who don't yet know where anything is documented
What's Included
- checkIndexing of existing documentation across your current tools
- checkNatural-language search that understands intent, not just keywords
- checkSynthesized answers drawn from multiple source documents, with citations back to the original
- checkAccess control so search results respect existing document permissions
- checkOngoing sync as source content changes
Frequently Asked Questions
Does this replace our existing wiki or docs platform?add
No — it sits on top of your existing documentation as a search layer, indexing content where it already lives rather than requiring a migration to a new platform.
How does it handle permissions?add
Search results respect the same access controls as the source documents — it doesn't surface content a given user wouldn't already have permission to see in the original system.
Does it cite where an answer came from?add
Yes — answers link back to the source document, so results can be verified against the original rather than trusted blindly.