How to Turn Your Company Documents Into an AI That Answers Instantly

Standard AI tools do not know your company. They do not know your PTO policy, your product pricing, your onboarding procedures, or your escalation workflows. When employees or customers ask company-specific questions, generic AI either makes things up or says it does not know.

Retrieval-Augmented Generation (RAG) solves this by grounding AI responses in your actual documents.

When a user submits a question, the system converts it to a vector embedding and searches your document library for semantically similar passages. The AI synthesizes an answer from those retrieved passages — with full source citations — rather than relying on its training data.

The result: answers that are accurate, company-specific, and auditable. You see exactly which document and page each answer came from.

HR teams deploy knowledge bots trained on employee handbooks and policy documents. Employees get instant answers about PTO, benefits, and payroll without creating tickets. Sales teams train bots on pricing sheets and competitive matrices so reps always have the right answer. IT teams build bots from runbooks so staff resolve issues without waiting for help.

Confidence scoring shows users how reliable each answer is. Source citation links directly to the document and page. Knowledge versioning lets you update training data anytime while preserving history for audits. Model selection lets you choose GPT-4o, Claude, Mistral, or local LLaMA per knowledge bot based on sensitivity and cost requirements.

MySynthos accepts PDFs, DOCX, TXT, and CSV uploads. It connects directly to Notion, Google Drive, SharePoint, and websites via crawler. Manual entry supports custom text and FAQ builder formats. Once indexed, your knowledge is queryable in seconds.