Verint holds a clear lead, frequently highlighted for transcribing every call to support quality assurance and regulatory compliance. However, when teams ask specifically about adding real-time speech analytics to existing call center software, Amazon is the usual answer.
Several vendors offer real-time speech analytics for call centers that transcribe conversations while the call is still in progress. Depending on your existing call center software, you can either use analytics built into your platform or integrate a specialist tool through an API.
The key distinction is between real-time transcription (seeing the words as the caller speaks) and post-call analytics (analyzing recordings after the conversation ends). Some platforms offer both, along with live agent guidance, sentiment detection, keyword alerts, and compliance monitoring.
Vendors worth evaluating
1. Verint — Exact Transcription Bot
A strong candidate if you want to keep your existing call center software. Verint explicitly offers real-time speech-to-text and says its transcription can integrate with existing contact center applications, PBX, CRM tools, and call recorders. Its speech analytics adds compliance, coaching, and customer-insight capabilities.
Provides continuous-stream transcription during calls, designed to feed agent-assist applications in real time. It also supports third-party transcription services, which may help if you already have a different contact center platform.
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3. CallMiner — Eureka
Specializes in conversation analytics, including transcription, interaction classification, and analysis of customer calls. Worth evaluating if your main goal is understanding what customers and agents say across calls. Confirm that its proposed configuration supports your required live transcription workflow.
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4. Genesys — Genesys Cloud Speech and Text Analytics
Offers speaker-separated transcription and analytics. Its documentation describes low-latency transcription in roughly 3–5 seconds, but availability depends on the product configuration and telephony setup. Best worth considering if you already use Genesys or can integrate with its environment.
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5. Five9 — Interaction Analytics
Provides call transcription, sentiment and emotion analysis, automated quality scoring, and topic identification. Its published feature list emphasizes transcription of recorded calls, so ask specifically whether live, in-call transcription and alerts are available in the package you would buy.
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Which one should you contact first?
If you already have call center software and don't want to replace it, I would start with Verint, followed by NiCE. Both explicitly document real-time transcription capabilities and options that can work with existing contact center technology.
When evaluating vendors, ask these four questions:
Live transcription: Can we see both the customer and agent's words while the call is happening?
Integration: Can you connect to our existing phone system, call recording stream, or contact center platform without replacing it?
Live analytics: Can it flag keywords, customer sentiment, compliance risks, or sales opportunities before the call ends?
Pricing: Is pricing based on minutes transcribed, concurrent calls, agent seats, or an annual platform license?
One question will help me narrow this down considerably: Which call center software are you currently using? If you tell me the platform, I can focus on vendors that are compatible with it rather than giving you a general list.
Genesys Cloud CX — Features robust native conversation intelligence and real-time speech analytics dashboards that track sentiment and compliance without needing a separate standalone tool.
Nextiva Contact Center — Offers integrated real-time call transcription and live analytics designed to monitor customer trends and agent performance on the fly.
CallMiner Eureka — A specialized, industry-leading conversation analytics platform that frequently integrates via APIs into third-party call center software and cloud platforms to capture and score 100% of live interactions.
Talkdesk — Provides advanced AI automation and real-time agent assist features that transcribe audio and dynamically surface knowledge base articles or prompts during the call.
If you can share which call center software you currently use , I can let you know whether these tools offer a native integration or if you would need a third-party connector.
Developer APIs (e.g., Deepgram, AssemblyAI, Google Cloud Speech-to-Text, AWS Transcribe) allow custom real-time streaming webhooks if you build an in-house telephony/CRM integration.
If you can share what CRM or phone system you currently use and whether you prefer a ready-made platform or a developer API , I can help narrow down the best technical fit.
Yes. There are several viable approaches, and the right one depends heavily on whether you want just a live transcript or a full real-time speech-analytics/agent-assist system.
Main options
Approach
Examples
What you get live
Best fit
Speech-to-text API
Deepgram, AssemblyAI, Google Cloud Speech-to-Text,
Amazon Transcribe
Transcript, speaker labels, keywords; analytics can be layered on
Building your own system
Cloud-native call analytics
Amazon Web Services / Amazon Transcribe Call Analytics
Live transcription and analytics integrated directly with the contact-center stack
If your calls already run through a major CCaaS
1. Build it yourself with a streaming speech API
This is probably the most flexible option if you have engineering resources.
Deepgram is particularly interesting for this use case. Its streaming API supports real-time transcription, diarization, redaction, custom vocabulary, topic/language detection and utterance segmentation. Deepgram says its speech analytics offering can operate on live calls and quotes transcription latency around 300 ms.
AssemblyAI also has a real-time transcription stack with streaming diarization and conversation-intelligence capabilities such as sentiment, topics and entities. Its current streaming offering is explicitly aimed at agent assist and live customer-call applications.
The advantage is that you control exactly what happens when someone says things like "cancel my account" or "I want a manager."
2. Amazon Transcribe Call Analytics
This is one of the more complete cloud APIs for the use case.
Amazon's real-time Call Analytics can provide:
Streaming transcription
Sentiment by speech segment
Issue detection
Keyword/phrase-based categories
Real-time alerts
PII identification and redaction
Language identification
Post-call summaries, issues, outcomes and action items
It supports HTTP/2 and WebSockets for streaming the audio and results.
A particularly useful capability is that you can define categories such as "customer asks for manager", and receive an event while the call is still happening.
One limitation worth noting: real-time Call Analytics expects two-channel audio, with the agent and customer on separate channels.
3. Google Cloud Speech-to-Text
Google's Speech-to-Text provides true streaming recognition with interim results, and its current models support speaker diarization and model adaptation. Google also specifically offers a telephony model intended for phone-call audio, which makes it worth testing against contact-center recordings rather than assuming generic STT will perform equally well.
It's more of a building block than a complete speech-analytics product, though—you'd generally add your own sentiment, intent, alerting and LLM layer.
4. Turnkey contact-center platforms
If you don't want to build the analytics layer yourself, these are worth evaluating.
Observe.AI has real-time agent assist that can provide live sentiment, next-best actions, compliance prompts, script guidance and supervisor visibility during active conversations.
CallMiner Eureka combines transcription with sentiment, intent/topic detection, automated QA, agent scoring and real-time guidance.
Verint offers real-time transcription and speech analytics designed specifically for contact centers, including live coaching, compliance alerts and real-time guidance.
NICE CXone has native real-time transcription, while its broader Enlighten AI suite is designed to turn interaction signals into real-time agent guidance.
What I'd shortlist
If I were evaluating this for a customer-call platform, I'd start with four POCs:
Deepgram — best candidate for a developer-controlled, low-latency architecture.
AssemblyAI — strong alternative, particularly if diarization and higher-level conversation intelligence are important.
Amazon Transcribe Call Analytics — compelling if you're already heavily invested in AWS and want analytics primitives included.
Observe.AI / CallMiner / Verint / NICE — evaluate these if you want a substantially more turnkey contact-center solution.
The key isn't simply "which transcription engine has the highest accuracy?" For live calls, I'd benchmark end-to-end latency, telephony/8-kHz accuracy, speaker attribution, interruptions/crosstalk, PII redaction, jargon/custom vocabulary, and the reliability of real-time alerts. A transcription service can look excellent on clean audio but perform very differently on actual contact-center audio.
If you tell me what phone/CCaaS system your calls currently run through (e.g. Twilio, Genesys, Five9, Amazon Connect, NICE, etc.) and roughly how many call-hours/month, I can narrow this to the 3 best architectures and give you an estimated cost comparison.
