Understands · live conversation
An AI prompter in the live conversation
The AI secretary answers the inbound call, qualifies it and transfers it to a live operator — but it doesn't hang up, it stays on the line. While the conversation continues, the operator sees a context summary on screen, a prompt for the next step and warnings, while the collected fields and transcript flow into the CRM on their own. The human runs the conversation, the AI takes the notes — nothing needs to be filled in after the call.
The problem
On a live call the operator has to listen to the customer, recall the context, look up an answer and try to write it all down at once. Something gets lost: half the CRM card is filled in later from memory, and important details — the amount, the deadline, the promise — get confused or forgotten. The conversation moves faster than a person can think and record.
An ordinary voice bot only shifts the problem: it answers the call and transfers it to a human, but at the moment of transfer it disconnects. The operator gets a "cold" call with no context and has to ask again for what the customer already told the bot — and the conversation starts over.
As a result the quality of live conversations depends on the memory and experience of the specific operator, not on the system. There's no prompt at the right moment, no risk warning, no guarantee the call will be recorded correctly in the CRM. Every conversation is a bet on a person with no safety net.
How the platform solves it
- 1
The secretary answers and qualifies
The AI secretary answers the inbound call to your scenario, runs the dialogue in the customer's language and collects the needed data into fields with required flags and validation.
- 2
Transfer to the operator — without losing context
Per your transfer rules the agent hands the call to a live operator and stays in the conversation (conference) instead of disconnecting: the context is already gathered.
- 3
The operator sees prompts in real time
On the operator's screen — a context summary, the next action, warnings and the already collected fields. The prompts update as the conversation goes, from the live transcript.
- 4
The recording is analyzed on the fly
The conversation is transcribed in real time; metrics, topics and data extraction feed the prompts, and after the call the recording flows into the shared analysis loop.
- 5
The outcome straight into the CRM
After the call the collected fields, notes and transcript have already been pushed to the CRM via the crmPush action — no need to fill in the card by hand.
The result
The operator runs the conversation with full context and a prompt at the right moment, while the system guarantees every call is recorded correctly in the CRM — with no manual back-fill.
- No "cold" transfer: the operator picks up the conversation with a ready summary instead of asking the customer everything again.
- A next-step prompt and risk warnings — right during the conversation, not in a post-call review.
- Collected fields and the transcript flow into the CRM automatically — the card is filled in with no manual work after the call.
- Every live conversation lands in analytics: metrics, topics, auto-tags — control across 100% of calls.
Key facts
- The key differentiator
- After the transfer the agent stays on the line in conference mode — it doesn't disconnect but switches to prompting the operator.
- What the operator sees
- A context summary, the next action, warnings and collected fields — in real time from the live transcript.
- After the call
- Collected fields, notes and the transcript are pushed to the CRM via the crmPush action — with no manual back-fill of the card.
- The mechanics
- Live call monitoring: real-time transcription, metrics and topics feed the on-screen prompts.
- Closes the flywheel
- Recordings of the conversations land in the shared analysis loop — the same data later improves the secretary's scenarios.
FAQ
Frequently asked questions
What does "stays on the line after transfer" mean?
After the secretary transfers the call to a live operator, it doesn't disconnect but stays in the conversation (in conference mode), keeps recording and switches to prompting mode: it shows the operator a context summary, the next step, warnings and the already collected fields. This is the core of the AI secretary pitch.
Does the operator get the customer with no context?
No. By the moment of transfer the secretary has already qualified the call and gathered the needed data, so the operator picks up the conversation with a ready summary on screen — there's no need to ask again for what the customer told the bot.
Where do the prompts during the conversation come from?
From live call monitoring: the conversation is transcribed in real time, and metrics, topics and data extraction form the context summary, the next-action prompt and the warnings right on the operator's screen.
Do I need to fill in the CRM manually after the call?
No. The fields, notes and transcript collected in the dialogue are pushed to your CRM automatically (the crmPush action finds the contact by number and writes the data), so the card is ready right after the conversation.
How does this connect to the rest of the platform?
Every conversation lands in the same analysis loop as all calls: transcription, metrics, topics, auto-tags, dashboards and semantic search. The data and knowledge from live calls flow back into tuning the secretary's scenarios — the flywheel closes.
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