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AI Reply Assistant

The AI Drafts the Reply Before You Type a Letter

The moment a customer message lands, the AI drafts three separate replies. It reads the intent, summarises the conversation and pulls from the customer card and your knowledge base. Your team picks one, approves it, and sends. The feedback you give teaches the tool your way of writing over time.

Short answer

When a customer message arrives, the AI drafts three replies from the conversation summary, the intent and your knowledge base. Your team picks and approves one. The AI that writes the suggestion never messages the customer on its own. Your feedback brings the drafts closer to your tone.

app.chatinbox.net/inbox/conversation/482
ZY

Zeynep Y.

AI active

Hi, how many sessions does implant treatment take?

14:23

AI suggestion · Intent: treatment process question

Live preview

The reply is ready the moment the message arrives

Your team picks with one tap and the answer goes out. Look at this example:

ZY
Zeynep Y.
WhatsApp · online
AI Active
Hi, when will the item I ordered yesterday arrive?
14:23
app.chatinbox.net/inbox/482

Conversation summary & intent

SUMMARY 12 messages · 8 min

Customer wants black shoes in size 42. Unsure about the size (42 or 43), delivery within Istanbul, wants to pay by bank transfer. Tone stays positive.

Intent

PURCHASE

92%

Objection

SIZE

Medium

Urgency

HIGH

Deciding today

Satisfaction

8.4/10

Positive

⚡ Suggested next action

Share the size chart + explain the difference between sizes → closing offer

Three ready replies · conversation summary · intent reading

The AI weighs every incoming message against your knowledge base, sector patterns and the customer's history. It drafts three tones at once (formal, short, friendly). Your team taps to send or edits first. This page covers the suggestion side for agents; in the flows you build, the bot does send without your approval. Conversation summary, intent score and the suggested next step sit in the same panel.

  • Three drafts at once: formal · short · friendly
  • Conversation summary: catch the context of a long thread in seconds
  • Intent score: purchase, question, complaint, return or undecided

Automatic tags & an instant customer card

The AI reads the conversation and applies the tag itself (price question, campaign, undecided, follow-up needed). The conversation is matched to the right customer record. That person's card and earlier threads stay on the right side of the panel. Your team does not have to look for the history somewhere else.

  • Smart tags: topic, intent, customer profile and urgency together
  • Customer card and earlier threads stay open on the same screen
  • The agent who takes over reads the summary instead of the whole thread
app.chatinbox.net/inbox/482/sidebar

Customer card (auto-matched)

ZEYNEP Y. Follow-up
ChannelWhatsApp
First message12 March
TopicImplant price
OwnerMerve K.

AUTOMATIC TAGS

Price question Returning contact Undecided Follow-up needed

CONVERSATION HISTORY

3rd conversation · Previous topic: check-up appointment · Preferred channel: WhatsApp

app.chatinbox.net/agent-assist/learning

Feedback learning, this month

Sample panel
Return flow suggestions 94% ↑

142 approved · 8 edited · 0 rejected. Agent tone learned.

Size question suggestions 87% ↑

94 approved · 12 edited. Size chart template now added automatically.

Complaint flow suggestions 62% ↗

38 approved · 22 edited. AI apology tone too formal; learning a warmer version.

📚 Learned this month

  • • "Hocam" form of address (Turkish friendly tone)
  • • 5 new KVKK (Turkish data protection law) phrases
  • • Delivery times within Istanbul

Learns from feedback and sounds more like you over time

When your team approves, edits or rejects a suggestion, the AI learns from it. Over time it picks up your sector's terms, the way you talk to customers and your team's tone. Which suggestion was approved and where it was corrected counts as feedback. The drafts follow the way your team writes.

  • Keeps learning from approve, edit and reject signals
  • Sector-specific vocabulary grows on its own
  • Accuracy is tracked; the acceptance rate shows in the report

Knowledge base integration (RAG)

Load your PDF, Word or web page content into the system. When a customer asks something, the AI drafts from the documents you uploaded. Your team sees which document the draft rests on. The source feeds the suggestion, it does not limit it. The agent is the one who catches a wrong suggestion before it goes out.

  • Quotes directly from the documents you uploaded
  • The source document is listed next to the draft; approval stays with the agent
  • Cross-language search: a question asked in Turkish is found in an English document
Knowledge base details
app.chatinbox.net/inbox/kb-lookup

Customer question

"How many days do I have to return? Do I pay the shipping?"

Draft from the KB, the agent approves

Our return period is 14 days. For unused items with tags still attached, we cover the return shipping. For damaged or used items the shipping cost is paid by the customer.

Give your team a higher gear

Instead of typing into a blank box, your agent edits a ready draft and sends it. A new hire finds the clinic's saved replies and knowledge base in front of them from day one.

Let's review your message flow together in 15 minutes

Let's talk about what's scattered across which channel, and see together how your team would use Chatinbox.

We handle the setupWe train your teamYour WhatsApp number stays the same

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