Internal AI assistant for employees

An internal AI assistant is a corporate helper based on your internal materials (policies, manuals, documentation, wiki) via RAG (893): an employee asks in natural language ('how to file for leave?', 'what is the returns policy?') and gets an answer with a source link, without long searching through folders. It is useful for onboarding and daily work. Honestly about errors and verification, this is key: the assistant answers from your documents but can err, oversimplify or output something outdated (especially if documents are not updated). For critical topics — HR, legal, financial, security — the assistant's answer must be verified in the source, not taken as a final instruction. We provide source links exactly for this. Honestly about privacy and access, this matters: internal data is often sensitive, so access control (which employees can ask what and which documents are visible to the assistant for a specific role) and privacy (where data goes — we discuss private/local options if documents are confidential) are critical. You cannot thoughtlessly open everything to everyone. Honestly about quality: answers depend on the quality and freshness of the internal base ('garbage in — garbage out'); part of the work is helping structure and maintain it. Honestly about the effect: it saves time on finding information and speeds up onboarding but does not replace experts and those responsible for critical decisions. Honestly about cost: answers are paid per token. Honestly about access: internal materials and an understanding of roles/access are needed. An important boundary: this is an internal employee assistant; a knowledge-base assistant (customer/general) — 868; support agent assistant — 883; RAG — 893. Picture this: instead of 'search the policy yourself through folders and ask colleagues' — ask and get an answer with a link, verifying the important. The base price starts from 55,000 ₽ (depends on base volume and access).

• Employees spend a long time searching policies and manuals in folders.
• Onboarding newcomers is slow, many questions to colleagues.
• Knowledge is scattered, the same questions are answered by hand.
• Fear for the confidentiality of internal data in AI.

• An AI assistant over internal documents (RAG — 893)
• Natural-language answers with a source link
• Role-based access control (who can ask/see what)
• Data privacy (private/local solution options)
• Honest boundaries (verify the critical in the source)
• Quality dependence on base freshness
• Help structuring the internal base
• Handover and review with you

• Fast answers on internal policies with a link
• Faster onboarding and daily work
• Access control and privacy accounted for
• Honest boundaries (verify the critical; not an expert replacement)

• We collect the internal base, define roles and access; clarify privacy
• We set up RAG, source links, access control
• We test answers, honestly set boundaries for the critical with you

• Can the assistant's answers be fully trusted?

  For critical topics — no, verification in the source is needed. The assistant answers from your documents but can err, oversimplify or output something outdated. For HR, legal, financial questions and security the answer must be checked against the original — that is exactly why we provide source links. The assistant speeds up search but does not replace those responsible for critical decisions.

• Is it safe to upload internal documents into AI?

  Only with access control and privacy, and we build that in. Internal data is often sensitive, so it matters: which employees can ask what, which documents are visible to the assistant for a specific role, and where data goes. For confidential materials we discuss private/local options. You cannot thoughtlessly open everything to everyone — that is a leak risk.

• Will the assistant know everything about the company?

  Only what is in the uploaded internal base, and as far as it is current. If a document is not updated or absent — there will be no answer or it will be outdated ('garbage in — garbage out'). So value depends on the base's quality and maintenance. Part of the work is helping structure it; but the assistant will not become an all-knowing expert, and we honestly state this.