AI Speech Analytics Visualization
CCaaS Intelligence Report · February 2026

Genesys Cloud AI:
Transcription & Sentiment

A deep-dive analysis benchmarking Genesys Cloud's speech and text analytics capabilities against industry standards and key competitors.

18
Vendors Analyzed
12
Features Compared
142
Market Leader Languages
20
Genesys Sentiment Languages
01

Executive Overview

Genesys Cloud Speech & Text Analytics

What Genesys Cloud Offers

Genesys Cloud CX delivers Speech and Text Analytics (STA) as an integrated AI capability within its WEM suite. The platform provides both native transcription and an Extended Voice Transcription Service (EVTS) leveraging third-party engines for broader language coverage. Sentiment analysis classifies customer phrases as positive, negative, or neutral, while the unique Agent Empathy Analysis evaluates agent emotional intelligence — a differentiator not found in all competing platforms.

Native + Extended Voice Transcription (EVTS)
Real-time & post-call sentiment analysis
Agent empathy analysis (unique differentiator)
PCI/PII sensitive data masking
Topic mining & intent detection
Bring Your Own Transcription (BYOT) support

Overall Competitive Score

Amazon Connect88/100
Google CCAI88/100
TalkDesk88/100
NICE CXone85/100
Twilio85/100
Sprinklr85/100
RingCentral83/100
Five983/100
Verint82/100
Microsoft D36582/100
8x880/100
Odigo80/100
Zoom CC80/100
Genesys Cloud78/100
Avaya70/100
Salesforce72/100
Cisco Webex65/100
Infosys IIA60/100

Composite score across transcription, sentiment, language support, and integration. Based on publicly available data and independent benchmarks.

Key Finding: Genesys Cloud is a capable and well-integrated platform for speech and text analytics, but it trails industry leaders in transcription accuracy benchmarks and language breadth. Its standout differentiator is Agent Empathy Analysis, which provides a unique dimension of interaction quality measurement not commonly found in competing platforms. Organizations requiring the broadest language support or highest raw transcription accuracy should evaluate Amazon Connect Contact Lens as a primary benchmark.

02

Transcription Capabilities

Accuracy, architecture, and language support

Transcription Modes
3
Native, EVTS, BYOT
Delivery Latency
3–5s
Post-segment delivery
Speaker Diarization
Yes
Agent vs. customer

Transcription Accuracy Benchmark

Word Error Rate (WER) derived accuracy on 8kHz call center audio. Source: Voicegain 2025 Benchmark. Genesys estimate based on community reports.

65%73%81%95%VerintTalkDeskGoogle CCAIAmazonConnectNICE CXoneFive9SprinklrRingCentralTwilio8x8Microsoft D365Zoom CCOdigoGenesysCloudAvayaCisco WebexSalesforceInfosys IIA90%90%90%87.7%88.5%88%87%86%86%85%85%84%84%83%80%78%75%72%

Genesys Transcription Architecture

1
Native Engine: Genesys-built ASR optimized for contact center audio. Low latency, tightly integrated with STA platform.
2
Extended Voice Transcription Service (EVTS): Third-party engine (phased rollout by language group). Expands dialect coverage beyond native engine.
3
BYOT (Bring Your Own Transcription): Connect any third-party STT provider via the Transcription Connector. Unique capability not offered by most competitors.

Known Limitations

ACD agent consult recordings are not transcribed
Transcription not available in all supported UI languages
Blind transfer recommended to avoid double-billing on transfers
No public independent accuracy benchmark available
Token-based pricing model adds cost complexity
Some languages only available via EVTS (phased rollout)
03

Sentiment Analysis Deep-Dive

Capabilities, methodology, and competitive radar

Sentiment Capability Radar

Relative capability scores (0–100) across key sentiment analysis dimensions.

Real-time AnalysisPost-call AnalysisAgent EmpathyLanguage SupportAccuracyAPI / Integration0255075100
  • Genesys
  • Amazon
  • NICE
  • Verint
  • Google
  • TalkDesk
  • Microsoft
  • Sprinklr

How Genesys Sentiment Works

Genesys Cloud's sentiment engine analyzes customer phrases at the utterance level, classifying each as Positive, Negative, or Neutral. Scores are aggregated to produce an overall interaction sentiment score.

The Agent Empathy Analysis layer evaluates agent phrases independently, classifying them as Empathetic or Unhelpful — providing a dual-track analysis unique in the market.

Sentiment Analysis Coverage

Voice (Post-call)
SupportedReal-time
Chat / Messaging
SupportedReal-time
Email
SupportedPost-only
Social Media
SupportedPost-only
Agent Empathy
SupportedReal-time

Language Support for Sentiment Analysis

Number of languages supported for conversational analytics / sentiment analysis per vendor.

TalkDeskGoogle CCAIOdigoSprinklrMicrosoft D3658x8NICE CXoneVerintZoom CCFive9SalesforceAvayaCisco WebexTwilioRingCentral04080120160
04

Competitor Deep-Dive

Head-to-head analysis against key platforms

Amazon Connect (Contact Lens)

AWS Ecosystem

Amazon Connect Contact Lens is the strongest technical benchmark for transcription accuracy and language breadth. Its 2025 benchmark accuracy of 87.7% on 8kHz telephony audio sets the industry bar. The platform's deep AWS integration is both its greatest strength and its primary lock-in risk.

Strengths

  • +Industry-leading transcription accuracy (87.7% on 8kHz call center audio)
  • +Real-time and post-call sentiment with per-turn scoring
  • +Broadest language support: 67 languages for conversational analytics
  • +Deep AWS integration (Lambda, S3, Comprehend, Lex)
  • +Supervisor real-time alerts on negative sentiment

Weaknesses

  • No native agent empathy analysis (requires custom build)
  • Tightly coupled to AWS ecosystem — limited portability
  • No BYOT (Bring Your Own Transcription) option
  • Pricing complexity with multiple AWS service costs

Capability Scores vs Genesys

Transcription88 vs 83
AmazonGenesys
Sentiment87 vs 80
AmazonGenesys
Languages95 vs 65
AmazonGenesys
Integration92 vs 82
AmazonGenesys
05

Infosys Informative Analytics (IIA)

Enterprise AI analytics for contact center intelligence

Platform Overview: Infosys IIA is an enterprise-grade AI analytics capability delivered by Infosys as part of their contact center intelligence portfolio. It combines NLP, conversational analytics, and post-call intelligence to surface call intent, customer sentiment, and root cause analysis. IIA is positioned as a composable AI layer that can augment existing CCaaS platforms, with deployment options on AWS and Red Hat OpenShift for organizations requiring on-premise or private cloud hosting.

IIA

Core Capabilities

AI analytics and NLP for contact center intelligence

Conversational analytics: call intent, customer sentiment, and root cause analysis (RCA)
Post-call transcription and NLP analysis via composite AI on AWS
Semantic search and document classification across organizational repositories
Sentiment and subjectivity analysis via REST API
Digitize-Recognize-Organize framework for contact center intelligence
Enterprise-scale document and email NLP with knowledge graph mining
Deployable on Red Hat OpenShift (on-prem or private cloud)
Demonstrated in production at TSB Bank (AWS-based deployment)

Differentiators & Considerations

What sets IIA apart and what to evaluate

Composable AI layer — augments existing CCaaS platforms (Genesys, Amazon Connect)
Strong back-office NLP: document classification, email automation, knowledge graph
On-premise and private cloud deployment for data sovereignty requirements
SI-delivered model allows deep customization to enterprise-specific terminology
Real-time voice transcription during live calls requires integration with host CCaaS
Live supervisor alerting and WFM integration depend on the host CCaaS platform
No independent public benchmarks available for transcription accuracy as of Feb 2026

IIA vs. Genesys Cloud: Capability Comparison

Real-time Voice TranscriptionIIA augments host CCaaS
IIA
40
Genesys
83
Post-call Text AnalyticsComparable
IIA
72
Genesys
75
Document / Email NLPIIA strength
IIA
82
Genesys
40
Sentiment AnalysisPost-call focus
IIA
68
Genesys
80
Back-office AutomationIIA differentiator
IIA
80
Genesys
45

Best Fit Scenarios for IIA

Infosys IIA is best suited for organizations that need:

Enterprise NLP for back-office email, document, and knowledge management
A composable AI layer to augment an existing Genesys Cloud or Amazon Connect deployment
On-premise or private cloud deployment for regulatory or data sovereignty requirements
Deep customization via an SI engagement with Infosys-managed model tuning
Unified analytics spanning voice interactions and document repositories
06

Feature Comparison Matrix

Side-by-side feature availability across all platforms

FeatureGenesys CloudAmazon ConnectNICE CXoneVerintSalesforceTalkDeskCisco WebexAvayaGoogle CCAIRingCentralTwilioSprinklrFive98x8OdigoZoom CCMicrosoft D365Infosys IIA
Real-time Transcription
Post-call Transcription
Sentiment Analysis
Agent Empathy Analysis
PII/PCI Redaction
Topic Mining
Intent Detection
Real-time Translation
Custom Vocabulary
Speaker Diarization
Supervisor Alerts
BYOT / Custom Engine
07

Architect's Verdict

Recommendations for CCaaS decision-makers

🟠 Choose Genesys Cloud When…

  • Agent empathy analysis is a priority KPI
  • You need BYOT flexibility for custom STT engines
  • Deep WEM integration (WFM, QM, coaching) is required
  • You are already invested in the Genesys ecosystem
  • Multi-channel analytics (voice, chat, email, social) in one platform

🟡 Consider Amazon Connect When…

  • Transcription accuracy is the primary requirement
  • Broad multilingual support (67 languages) is needed
  • Deep AWS ecosystem integration is a strategic goal
  • Real-time supervisor alerting on sentiment is critical
  • Pay-per-use pricing model is preferred

🟣 Consider NICE CXone When…

  • 100% interaction coverage for sentiment is required
  • Domain-specific AI (complaint, sales, CSAT) is needed
  • Real-time translation is a core requirement
  • Strong WFM + AI scheduling integration is a priority
  • You want AI trained on decades of CX-specific data

🔵 Consider Google CCAI When…

  • Best-in-class NLP and language support (152 languages) is required
  • You are building on Google Cloud infrastructure
  • Dialogflow CX virtual agents are part of the strategy
  • Deep BigQuery/Vertex AI analytics integration is needed
  • You want hyperscaler AI without AWS lock-in

🟣 Consider TalkDesk When…

  • Broadest language support (194 languages) is a hard requirement
  • No-code AI model customization is needed (AI Trainer)
  • Mid-market budget with enterprise-grade AI features
  • Comprehensive AI suite without hyperscaler complexity
  • Strong PII redaction and compliance are priorities

🟡 Consider Sprinklr When…

  • Unified CXM across social, digital, and voice is the goal
  • BYOT (Bring Your Own Transcription) is required
  • 100+ language sentiment analysis is needed
  • Social listening and contact center analytics must be unified
  • Custom ASR model fine-tuning is a priority

🟢 Consider Infosys IIA When…

  • A composable AI layer to augment Genesys Cloud or Amazon Connect is required
  • Enterprise NLP for back-office email, document, and knowledge management is a priority
  • On-premise or private cloud deployment is a hard regulatory requirement
  • You are engaged with Infosys as a strategic SI partner
  • Unified analytics across voice interactions and document repositories is needed

Summary Assessment

Genesys Cloud's transcription and sentiment capabilities are solid and well-integrated within its broader CX platform, but they do not lead the market on raw technical benchmarks. The platform's most distinctive AI capability — Agent Empathy Analysis — provides a dimension of quality measurement that most competitors lack, making it particularly valuable for organizations focused on agent coaching and quality management programs.

The introduction of the Extended Voice Transcription Service (EVTS) and BYOT support demonstrates Genesys's recognition that a single transcription engine cannot serve all use cases. However, the lack of publicly available independent accuracy benchmarks makes objective comparison difficult. For contact center architects, the recommendation is to run a proof-of-concept with real interaction audio before committing to any platform's transcription claims.