Speech analytics is automatic call analysis: the technology turns phone conversations into text and scores call quality, tone of voice, script compliance, conversion and churn risk. Unlike manual listening, it reviews 100% of calls rather than a sample; with manual quality control, by McKinsey’s estimate, fewer than 5% of conversations get checked. The system separates the agent’s and the customer’s lines, gives each call an AQS quality score from 0 to 100 and writes the outcome into the CRM record. In Uzbekistan the key question is language: customers speak Uzbek, Russian and a mix of both, so Uzbek speech recognition matters more than any generic metric. Zukko.AI analyses calls in Uzbek, Russian and English; the Start plan covers up to 300 reviews a month, the Business plan lifts that limit, and a small business can start without IP telephony, recording calls on the manager’s phone. Onboarding takes from 2 hours for a small business and up to 30 days for an on-prem enterprise.
the Zukko.AI speech analytics module
If your call centre or sales team handles hundreds of calls a day, you are almost certainly listening to only a handful of them. This guide explains how AI call analysis works, which metrics it produces, whether it understands Uzbek speech, and which kinds of solutions are already available in Uzbekistan. It is a hub: every section has its own detailed article, linked along the way.
What speech analytics and automatic call analysis are
Speech analytics is the AI review of phone conversations: the system transcribes a recording, labels who is speaking and evaluates the content. Automated review covers 100% of calls, while a manual sample, by the estimate of McKinsey, covers less than 5%. “Automatic call analysis” and simply “call analysis” are everyday names for the same process.
The difference between the two terms is one of emphasis rather than substance. “Call analysis” is usually said about sales tasks: a lost deal was found, a script was checked. “Speech analytics” is the more systematic term: quality, tone, conversion and churn risk across the entire flow of calls.
Modern speech analytics answers four business questions:
- What was said? A full transcript split into agent and customer.
- How was it said? Tone of voice, emotions, pauses, interruptions.
- Was it by the rules? Script compliance, mandatory phrases and stop phrases.
- What happens next? Call conversion, the reason for a refusal, the customer’s churn risk.
Speech analytics automatically transcribes and scores phone calls: the text of the conversation, tone of voice, script compliance and conversion. It covers 100% of calls against less than 5% with a manual sample (McKinsey estimate), so it replaces spot-check listening with a review of the whole flow.
Automatic call analysis: what it is
Automatic call analysis is the processing of call recordings without human involvement: the system transcribes every call, separates the agent’s and the customer’s turns, checks script compliance, scores the tone and outcome of the conversation, and writes the result to the CRM. The whole flow is checked rather than a sample, so a manager sees the real picture for every agent.
| Parameter | Spot-check listening | Automatic analysis of 100% of calls |
|---|---|---|
| Coverage | A small share of calls — less than 5% by McKinsey’s estimate | Every call |
| Who scores | A supervisor, by ear | AI on a single scale |
| How calls are selected | By hand: more often short and recent ones | No selection — the whole flow |
| Speed | Days or weeks after the conversation | Shortly after the call ends |
| Result | A score for individual conversations | Trends by agent, script and refusal reason |
| The human role | Listens and fills in a checklist | Reviews the calls the system flags and coaches the team |
how to assess a call centre agent without manual QA
Why manual quality control no longer keeps up
Manual quality control checks less than 5% of calls, and even that sample is scored with 70–80% accuracy against more than 90% for automated scoring (McKinsey estimate). When a supervisor listens to a few dozen calls out of a thousand, the whole team is judged by a random handful of recordings. The problem conversations almost always stay outside the sample.
The numbers show the scale of the pain. A large bank call centre can take more than 500 calls a day, and most of them are never checked by hand. The direction is clear: manual QA physically does not scale.
This is where the main risk of sampling lies, and it is not only about volume. People do not pick calls at random: they pick short, recent, convenient ones. So manual QA does not just cover little — it covers with a bias. Speech analytics removes both limits at once: 100% of the flow and a single scoring scale.
Manual call quality control checks less than 5% of conversations with 70–80% accuracy, while speech analytics reviews 100% of calls with more than 90% accuracy (McKinsey estimate). The sample is also biased: people pick convenient calls, not representative ones.
call quality control: from a sample to a 100% review
How speech analytics works: four steps
Speech analytics follows the same path from a call to a decision, and it does so for 100% of conversations. The process fits into four steps: intake of the recording, transcription, analysis, action. Each step is automated and never requires a person to open an audio file.
- Call intake. The recording arrives from a PBX, cloud telephony or a recorder app on the manager’s phone.
- Transcription. The system converts speech to text and labels who is speaking (diarisation), in Uzbek, Russian or English.
- Analysis. AI assesses tone, script, emotions and conversion, and calculates quality metrics on a single scale.
- Action. The result is written to the CRM, the agent receives a score, and the supervisor gets a summary and trends.
One detail matters specifically for Uzbekistan: the transcription step was the bottleneck for a long time. Global systems understood Russian and English well but stumbled on Uzbek speech and on mixed Uzbek-Russian speech.
Which metrics call analysis gives sales and support teams
Good speech analytics turns a conversation into numbers a manager can see: a quality score, conversion, churn risk. The logic is simple: when the entire flow of calls is reviewed, lost deals and script errors surface, and that directly lifts conversion and service quality.
The basic set of metrics to expect from a system:
| Metric | What it shows | Who needs it |
|---|---|---|
| AQS 0–100 | Agent Quality Score: an overall quality score for the call | Supervisor, QA |
| Call conversion | The share of calls that lead to the target action | Sales team |
| Tone of voice | The emotional colouring of the conversation | CX, support |
| FCR | The issue is resolved on the first contact | Support |
| CSAT / CES | Customer satisfaction and customer effort | Head of CX |
| Churn risk | Signals of dissatisfaction and of a customer about to leave | Retention |
The main value is not any single metric but the single scale. When every call is scored the same way, you can fairly compare agents, weeks and campaigns. In Zukko.AI this is AQS 0–100 and a model of 20 tones of voice, tied to churn, CSAT, FCR and CES. That is no longer “listening to a call” — it is managing quality from a dashboard.
Does speech analytics work in the Uzbek language
Yes, and this is the main shift of the past year and a half. Uzbek support in global speech systems has historically been limited: they handled Russian and English far better than Uzbek speech. Then Uzbek-language solutions appeared on the local market, and Uzbek speech-to-text with analysis of 100% of calls became a reality.
Here is why it matters strategically. Most well-known speech analytics systems come from Russia or from the global market, and Uzbek speech is a blind spot for them. Businesses in Uzbekistan talk to customers in Uzbek and in a mixed Uzbek-Russian mode. Without Uzbek speech-to-text, a large part of the conversation simply goes unanalysed.
Uzbek-language solutions are already at work today:
- State-run Uzbek-language services — Uzbek STT/TTS, analysis of 100% of calls, emotions and diarisation.
- Local commercial speech analytics solutions with high-accuracy Uzbek transcription.
- Open Uzbek speech corpora on which teams build their own models.
Uzbek support in global and Russian speech analytics systems has historically been limited. With the arrival of local Uzbek-language solutions, Uzbek transcription has matured enough to analyse 100% of calls. Zukko.AI recognises Uzbek, Russian and English with automatic language detection.
Uzbek call transcription in the Zukko.AI call analytics module
Which speech analytics solutions are available in Uzbekistan
The Uzbekistan market falls into two groups: local Uzbek-language players, and Russian or global systems without Uzbek speech. Search data gives a rough sense of the language mix: according to Statcounter figures for May 2026, Google held 74.6% of search in Uzbekistan and Yandex 22.4%, which suggests the Russian-language segment still carries weight. Below is a comparison by category of solution.
| Solution category | Uzbek speech | Data in UZ / on-prem | AQS 0–100 | Any PBX + recorder | Focus |
|---|---|---|---|---|---|
| Zukko.AI | Yes | Yes / yes | Yes | Yes | AI platform for sales and support |
| Local Uzbek services | Yes | Partly | Usually not | Partly | Uzbek-language call centre analytics |
| State-run services | Yes, strong | On-prem: yes | Usually not | Partly | State Uzbek-language analytics |
| Global / foreign services | No | Data stored abroad | Varies | Often their own PBX | Speech analytics without Uzbek |
Where Zukko.AI sits on this map. Local players are strong in Uzbek speech but narrower as products: they lack the link between AQS 0–100 and churn, CSAT, FCR and CES, the 20 tones of voice and the 30+ filters for searching conversations. Russian systems go deeper as products but do not understand Uzbek and store data outside Uzbekistan. Zukko.AI covers both sides: Uzbek speech plus platform depth, a connection to any PBX, and recording from the manager’s phone.
speech analytics in Uzbekistan: a 2026 market overview
speech analytics services compared and how to choose
Speech analytics for banks: data in Uzbekistan and on-prem
For banks and fintech, speech analytics is first of all a question of data and compliance. Banks in Uzbekistan are publicly ranked on call centre quality (Kursiv, 2025), and the voice of an identifiable customer is personal data under Law No. ZRU-547 “On Personal Data”. That is why regulated businesses ask for in-country storage and on-premises deployment.
The regulatory background is worth knowing. Amendment ZRU-1125 of 26 March 2026 relaxed mandatory localisation, keeping it for biometrics, genetic data and telecom subscriber data (gazeta.uz, 2026). A voice used to establish a customer’s identity is biometric data and is not covered by the relaxation; a recording made for quality control is usually treated as ordinary personal data (see our article on Law No. ZRU-547 for the detail). Banks, meanwhile, keep recordings in the country under their own security requirements.
In our experience of working with CIS banks, on-premises deployment and in-country data residency are the first question in a security review, ahead of price and features. Zukko.AI is deployed on-premises on the client’s infrastructure, with recordings stored in Uzbekistan. Such a rollout takes up to 30 days, including the security review and audit trail.
A customer’s voice is personal data under Law No. ZRU-547 “On Personal Data”, and amendment ZRU-1125 (26 March 2026) kept mandatory localisation for biometrics (gazeta.uz, 2026). Banks therefore generally require speech analytics to store recordings in Uzbekistan and to support on-premises deployment. Zukko.AI supports both.
speech analytics for banks, on-prem and data in Uzbekistan
How speech analytics differs from call tracking
These are different tools that are often confused. Call tracking answers the question “where did the call come from”; speech analytics answers “what was said inside the call, and how”. The first counts sources and the cost of a lead; the second examines the quality, tone and conversion of the conversation.
A short comparison to keep them apart:
- Call tracking — marketing: which channel and which ad brought the call, and what the lead cost.
- Speech analytics — sales and quality: what the agent said, whether the script was followed, whether the deal closed, whether the customer is satisfied.
- Together — the full picture: both where the call came from and what the manager did with it.
Call tracking shows which source a call came from; speech analytics examines what was said inside the conversation and how — quality, tone, script, conversion and churn risk. They are different layers: the first is about marketing and the cost of a lead, the second about sales and service quality.
speech analytics and call tracking: what the difference is
How to connect speech analytics without IP telephony
You can launch speech analytics even if you have no cloud PBX or IP telephony. For a small business this removes the main barrier to entry: there is no need to change telephony for the sake of analytics. Managers’ calls are recorded by an app on the phone and sent for review, and onboarding in this scenario takes from 2 hours when data and access are ready.
Two connection routes cover almost any business:
- You have a PBX or cloud telephony. Connect through a single webhook to any PBX, including Sarkor, which is already in production.
- You have no IP telephony. The Zukko Call Recorder app for Android collects call recordings from the manager’s phone and sends them for analysis.
This matters most for small businesses and sales teams that work from ordinary mobile phones. They do not need an expensive contact centre to begin reviewing calls. It is enough to install the recorder and connect the CRM. Launch takes hours, not weeks.
how to roll out speech analytics without replacing your telephony
Conclusion: where to begin
Speech analytics is no longer an option reserved for large call centres. When manual QA checks less than 5% of calls (McKinsey estimate), a full AI review becomes basic quality hygiene — for a bank and for a five-person sales team alike. The main barrier for Uzbekistan, Uzbek speech, has been removed: transcription has matured.
What this means in practice. If you are choosing a solution, check three things: whether it understands Uzbek speech, where it stores data, and whether it connects to your telephony without replacing it. Zukko.AI is an AI platform for sales and support that covers all three: Uzbek, Russian and English; data in Uzbekistan with on-premises deployment for banks; a connection to any PBX or recording from the phone. Get a demo call to see how it works on your own calls.
how much call centre call analysis costs
Frequently asked questions
What is speech analytics in plain words?
Speech analytics is AI that listens to every phone call for you. It turns the conversation into text, scores quality, tone and conversion, and writes the outcome to the CRM. Instead of the sample of less than 5% of calls that manual QA covers, the system reviews 100% (McKinsey estimate).
What is automatic call analysis?
Automatic call analysis is the review of call recordings without manual listening. The system converts each call to text, separates agent and customer turns, checks the script, scores tone and outcome, and passes the result to the CRM. Unlike spot-check listening, it covers the whole call flow, so agent scores are comparable with one another.
Does speech analytics work in the Uzbek language?
Yes. Uzbek support in global speech systems has historically been limited, but Uzbek transcription has now matured: local Uzbek-language solutions offer Uzbek speech-to-text and analysis of 100% of calls. Zukko.AI recognises Uzbek, Russian and English and detects the language during the conversation, so mixed Uzbek-Russian speech is transcribed in full.
Is consent needed to record calls?
A customer’s voice is personal data under Law No. ZRU-547 “On Personal Data”, so recording needs a notice or another legal basis. Common practice is a “this call is recorded” phrase at the start. Amendment ZRU-1125 (2026) kept mandatory localisation for biometrics (gazeta.uz, 2026). This is general information, not legal advice: agree the basis and wording with your lawyer.
Can speech analytics be connected to my PBX?
Yes. Zukko.AI connects to any PBX through a single webhook, including Sarkor, which is already running in production. If you have no IP telephony, the Zukko Call Recorder app for Android collects recordings from the manager’s phone. Onboarding for a small business takes from 2 hours when data and access are ready. Your telephony stays as it is.
How does speech analytics differ from call tracking?
Call tracking shows where a call came from and what the lead cost. Speech analytics examines what was said inside the conversation and how: quality, tone, script, conversion, churn risk. They are different layers: the first is about marketing, the second about sales and service quality. Together they give the full picture; one tool does not replace the other.
How many calls does speech analytics check?
100%. That is the main difference from manual quality control, which can physically cover less than 5% of conversations, and even those with 70–80% accuracy versus more than 90% for automated scoring (McKinsey estimate). The system scores the entire call flow on one scale, with no cherry-picking of convenient calls.
Where are call recordings stored?
It depends on the system, and for banks this is the deciding question. Russian and global services store data outside Uzbekistan. Zukko.AI stores recordings in Uzbekistan and, for banks, deploys on-premises on the client’s infrastructure. Recordings and transcripts then stay inside the bank’s perimeter, and the bank itself configures access to them.