In this article
Your team answers integration questions, explains requirements and agrees exceptions in Telegram and Slack. Those answers stay in individual chats, while colleagues keep asking the same questions.
Useful answers get buried in the conversation
A technical expert explains an integration in one client group. Another salesperson needs the same explanation a week later. Finding the right chat, date and person takes work, even when the company still has access to the conversation.
A shared FAQ keeps the question, the answer and its context together. Colleagues can reuse the explanation and see which terms apply only to a particular client.
Start with one question the team repeats
Choose work chats your team can access and one recurring topic: integration prerequisites, technical objections or information needed before a proposal. Build a useful set of answers on that topic, then add the next one.
Keep customer-specific terms separate from general explanations. An answer about one customer's deadline, infrastructure or commercial terms belongs to that customer's context. It should not silently become the default answer for the next prospect.
From client messages to a useful FAQ
Save the selected conversations in the company archive. Connect an approved AI tool to the available archive data through MCP. Ask it to group repeated questions, draft answers from the conversation and identify where the evidence is incomplete or contradictory.
A salesperson or subject expert then checks each draft against the original messages. Keep a reference to the source wherever the tool returns one; otherwise locate the original message before accepting the answer. Add an owner and a review date to answers that may change. Publish the reviewed FAQ in the knowledge base the team already uses.
Keep every answer connected to its source
Name the chats, date range and topic in your AI request. Ask for the messages behind each answer, customer-specific exceptions and questions still unresolved. A colleague should be able to open the source and understand when the answer applies.
Cerber keeps the conversation context available to your AI. An expert reviews the draft, and the team adds it to its existing knowledge base. Set up a separate integration if you want to update the wiki or CRM automatically.
Make the knowledge base part of daily work
Use the FAQ when preparing a proposal, answering a technical question or onboarding a salesperson. Include the source and any customer-specific terms so the next person can understand the answer without reconstructing the whole conversation.
Assign an owner to each topic. Update the answer when an integration, product requirement or commercial condition changes. Add new questions from work chats to keep the knowledge base close to what the team actually needs.
A question to try with your AI
Replace the fields in brackets with your details.
Review the selected client conversations about [topic] during [period]. Group recurring technical questions. For each, draft an answer supported by the messages and identify the source if available. Separate general guidance from customer-specific terms. Mark contradictions, missing history and unanswered questions. Do not invent a resolution.
Your working checklist
- The relevant questions and answers are saved in the archive.
- Customer-specific exceptions remain visible.
- An expert checks answers against original messages.
- Each approved answer has an owner and review date.