Company knowledge scattered across shared drives, PDFs and a handful of people's heads is a real drag on a growing team. A properly built internal chatbot lets staff ask a question in plain language and get an answer grounded in your own approved documents. Read this page in full before assuming a specific capability, several details here depend on your own document set and are confirmed during scoping, not guaranteed up front.
Retrieval-augmented generation (RAG) means the assistant searches your approved documents for relevant passages first, then writes an answer grounded in what it found, rather than answering from general knowledge alone. Done well, this means an answer can point back to the actual document and section it came from.
Confirmed per deployment. Commonly considered: PDFs, text documents, and scanned pages with OCR. Tell us your actual document types during scoping rather than assuming a format works.
How often the knowledge base refreshes when documents change is scoped to your needs, a rarely-updated policy library has different requirements than a fast-moving product spec.
The intent is answers traceable to a source document. Exact citation format and coverage is confirmed during scoping for your specific document set, this is not yet a blanket guarantee across every file type.
Access-control requirements, including any role or team-based restriction, need to be scoped with us directly for your document set and org structure before launch.
Before wider rollout, a small group should test the assistant against known-answer questions to check accuracy against your actual documents.
When a document is out of date or no relevant source is found, the assistant should say so rather than inventing an answer, confirm this fallback behaviour during scoping.
This runs on the same underlying platform as AI Convo's customer-facing chatbot, but configured as a separate, staff-only deployment. Internal company documents are never exposed to the customer-facing bot, and vice versa.
This is a scoped, conversation-first engagement, tell us what you're working with and we'll confirm what's genuinely feasible.
We'll scope feasibility before quoting anything.