Internal Q&A

Internal Q&A with AI Employees trained on company knowledge

AGTO turns FAQs, manuals, and past answers into approved AI skills for internal Q&A. Teams can reduce repeated questions while keeping people in the review loop.

SummaryWhat you will learn

Which data to prepare first for internal Q&A
How people review answers before they become reusable skills
How question logs improve FAQs and operating procedures

Internal Q&A

Turn questions into approved knowledge

Questions, answer candidates, reviewer checks, and approved skills are handled as one improvement loop.

AGTO channel where AI organizes and answers internal questions
1

Start from FAQs and work documents

You do not need to connect every document at once. Begin with the FAQs, manuals, policies, and past answers that match one team's repeated questions.

Start from FAQs and work documents
2

Do not publish raw AI answers

AGTO lets staff review, edit, approve, or reject answer candidates. Only approved knowledge becomes a reusable skill for future work.

Do not publish raw AI answers
3

Use question logs as improvement signals

Unanswered questions, repeated requests, and outdated documents become visible so teams can update FAQs and procedures continuously.

Use question logs as improvement signals

Internal Q&A

People approve answers, and approved skills are reused for future replies.

Approval-loop diagram: question, human review, approved skill, then reuse
1

Design Detail

Data to collect first for internal Q&A

Instead of connecting the whole company at once, scope to one team's questions and answer criteria. For each document type, decide what AI may see and what people must check.

Data typeHow it is usedWhat to check
FAQ / help articlesGenerate initial answer candidatesOutdated answers, exceptions, owning team
Manuals / policiesReinforce evidence and proceduresLatest version, access rights, team-specific differences
Chat / email answer historyExtract phrasing actually used in practicePersonal data, unofficial answers, individual judgment
Unanswered / sent-back logsFind knowledge that needs improvementMissing documents, unclear criteria, missing permissions
2

Design Detail

Criteria for turning answers into skills

Do not publish AI answers as-is; only those that reach a reusable level become approved skills. Separating criteria up front also helps estimate reviewer load.

DecisionStateNext action
ApproveEvidence is clear and exceptions can be explainedSave as a skill and reuse for future answers
Approve with editsUseful but wording or conditions are insufficientApply reviewer edits and skill it
HoldMissing evidence or decision ownerSpecify documents/team and re-check
RejectWrong answer, out-of-scope info, too many exceptionsDo not reuse; keep only the failure reason in the improvement log

Metrics

Metrics for an internal Q&A pilot

Rather than answer counts, look at whether knowledge became reusable in practice. Track duplicate questions, first-response time, approved skills, sent-back reasons, and documents that need updating.

01

Duplicate questions

Are the same questions recurring less

02

First-response time

Is the first answer getting faster

03

Approved skills

Are reusable approved answers growing

04

Sent-back reasons

Can rejects and edits be categorized

05

FAQ updates

Are documents that need updating visible

Process

How to roll out internal Q&A

1

Scope

Pick one work area

Start with HR, IT, sales support, admin, or another team with repeated questions.

2

Review

Review answer candidates

Staff check AI candidates and record approvals, edits, and rejects.

3

Reuse

Reuse approved answers

Approved skills support future Q&A and connected routines.

FAQ

Internal Q&A FAQ

Can we start with few FAQs?

Yes. Past chat answers, manuals, emails, and reviewer input can form the first skill set.

What happens when AI is wrong?

Reviewers can edit or reject the answer before it becomes official knowledge. The correction improves future skills.

Which team should start first?

Teams with repeated questions and clear answer criteria, such as HR, IT, admin, or sales support, are good candidates.

How is it different from internal search or RAG?

Search and RAG mostly help you find information. AGTO turns frequently used answers into approved skills after human review, then feeds them back into future questions and routines.

Can we check the source of an answer?

Yes, by design. Answer candidates keep their references, documents that need updating, and reviewer edits, and only approved answers are reused.

Do you measure more than ticket reduction?

Yes. We also track first-response time, reviewer load, FAQ updates, and the categories of questions that could not be answered.

Next Step

Pilot internal Q&A in a small scope

Share the target team, existing FAQs, and available documents. We can design a 2-week pilot scope.