C CallScribe

Industry solution

Conversational AI for sales teams and call centers

Leads go cold before a rep gets to the request, scripts are followed however it happens, and you only ever hear 2–3% of calls — so conversion drops out of sight. The platform calls new leads instantly with an AI qualification bot, checks 100% of calls against the script with auto-tagged objections, and builds coaching on objective data — interruptions, speaking pace, the rep's talk share. Sales gets control over every conversation, not a random sample.

Sales pains

Where sales and the call center lose money on calls

Leads go cold on slow callbacks

By the time a rep reaches the request, the lead has already talked to a competitor. Speed of the first touch drives conversion, but there's physically no one to call everyone back at once.

Call control is a 2–3% sample

A manager or the QA team gets to listen to 2–3% of calls. What reps actually say on the other 97% and why deals fall through stays out of view.

Scripts aren't followed

Required stages, objection handling and legal wording get skipped, and you can't catch that on a sample. The standard lives on paper, not in the conversation.

Coaching is subjective

Call reviews rest on an impression and a couple of recordings rather than data. Who to level up and on which skills is decided by feel, without objective conversation metrics.

What the platform gives you

Every pain is closed by a specific pillar

Instant callbacks and lead qualification

The AI qualification bot calls a new lead the moment it lands, holds a natural conversation, filters out non-target inquiries and hands live reps only warm, ready-to-talk contacts.

  • First touch on a new lead in minutes while it's still hot, not hours.
  • Qualification by need, budget and timeline — reps get only target contacts.
  • Reactivation of your dormant database on a script with no added headcount or manual dialing.

100% script QA with auto-tagged objections

Every call is transcribed automatically and checked against the script: stages passed and skipped, required wording, objection handling — with auto-tagged objections and risky spots.

  • Script checks on 100% of calls, not a 2–3% sample of what got listened to.
  • Auto-tags for objections, reasons for loss and compliance risks — by the meaning of the conversation.
  • Automations flag violations and send alerts on problem calls.

Coaching on data instead of subjective judgment

The conversation is broken down into objective metrics — interruptions, speaking pace, the rep's talk share, tone, the longest monologue. You see conversion by rep and stage, and who to level up on which skill.

  • Conversation metrics: interruptions, speaking pace, talk share, response latency, tone.
  • One picture of conversion by rep, stage and reason for loss.
  • Dashboards and rep-to-rep comparison — coaching on facts, not on an impression.

Funnel setup and review in plain language

The AI copilot assembles the set, metric or rule you need from a plain-language request: "show me calls where price-objection handling broke down." It also configures views, tags and automation rules without a data engineer.

  • A set of problem calls for review — from a plain-language request.
  • Setting up filters, tags and qualification rules in words, without manual configuration.
  • Semantic search across the whole archive: finds conversations by meaning, not by keyword.

Scenarios

How it works in sales and the call center

  1. 1

    A new lead — qualification and an instant callback

    A request lands in the system and the AI qualification bot calls right away: it clarifies the need, budget and timeline, filters out non-target inquiries and books the next step. While a competitor is still getting around to calling back, your lead is already qualified and hasn't had time to cool off.

    A warm, ready-to-talk contact is handed to a live rep along with the collected fields and transcript. The rep doesn't waste time on cold qualification, enters the conversation prepared, and the collected data flows into the record fields and your CRM.

  2. 2

    100% script QA with auto-tagged objections

    Every call is checked against the script automatically: the system marks stages passed and skipped, required wording, and how the rep handled an objection. The QA team sees not a 2–3% sample but the full picture across every conversation.

    Objections, reasons for loss and risky spots are auto-tagged by meaning, and automations send an alert on problem calls. Finding every conversation where, say, price-objection handling broke down takes one request to the copilot.

  3. 3

    Coaching reps on objective data

    The conversation is broken down into metrics: interruptions, speaking pace, the rep's talk share, response latency, tone, script adherence. A manager reviews not "it felt like it" and a couple of recordings but an objective picture per rep, and understands who to level up on which skill.

    Weak spots are found with semantic search and rep-to-rep comparison on dashboards, and the review runs on concrete calls. The copilot helps assemble the set you need with a simple request — for example, every call where the rep interrupted the customer and lost the deal.

Result

Sales and the call center stop working blind: every lead gets an instant touch, every call is checked against the script, and coaching is built on data, not on an impression.

  • An instant first touch on new leads instead of going cold on slow callbacks.
  • Control over 100% of calls against the script instead of a 2–3% sample.
  • Auto-tagged objections and risky spots — script violations don't get lost.
  • Coaching on objective conversation metrics instead of subjective judgment.

Key facts

Where to start
Upload your call archive or connect telephony — integrations aren't required for QA and coaching.
Coverage
100% of calls are checked against the script, not a 2–3% sample.
Outbound
The AI bot qualifies new leads with an instant callback and reactivates your database; warm contacts go to reps.
Coaching
Objective conversation metrics — interruptions, speaking pace, the rep's talk share, tone — instead of subjective judgment.
Data
Collected fields and transcripts flow into your CRM (Bitrix24, amoCRM/Kommo, RetailCRM, Megaplan).

FAQ

Frequently asked questions

Do I need a telephony integration to start?

No. For script QA and coaching it's enough to upload your archive of recordings. Telephony (MANGO OFFICE, Telfin, Sipuni, Zadarma, UIS and others) and the outbound AI bot are connected later, when you want to automate outbound calls.

How does the platform check script adherence across all calls?

Every call is transcribed and checked automatically: stages passed and skipped, required wording and objection handling are flagged, and objections and risky spots are auto-tagged by meaning. QA runs across 100% of calls, not a 2–3% sample, and alerts come in on problem conversations.

What is rep coaching built on?

On objective conversation metrics: interruptions, speaking pace, the rep's talk share, response latency, tone and script adherence — per rep and per stage. Weak spots are found with semantic search and dashboard comparison, and the review runs on concrete calls rather than on an impression.

How is the AI callback different from a press-a-key auto-dialer?

The AI bot holds a natural conversation, understands free-form answers and lets the customer interrupt it, rather than pushing them through a tree of touch-tone keys. It qualifies the lead by need, budget and timeline, collects data into fields, and hands a warm contact to a live rep.

Does call data flow into our CRM?

Yes. Collected fields, notes and transcripts are pushed into your CRM — Bitrix24, amoCRM/Kommo, RetailCRM and Megaplan are supported, plus an outbound webhook for any other system.

Ready to start?

Turn every conversation into data, knowledge and action

Start by analyzing your conversations — no risk, no bots required. The platform turns your archive into data and a knowledge base, and voice agents plug in when you're ready.

Free plan, no card required.