SentiSum

AI CX Intelligence for Voice of Customer, Root-Cause Analysis and Quality Assurance

 

SentiSum is AI-native CX intelligence software that analyzes customer conversations and feedback across support tickets, calls, chats, surveys, reviews, CRM notes, social channels, and AI-agent interactions and tells you what to fix, where you’re leaking, and what each fix is worth in dollars.

It helps Customer Experience, Support, Operations, Product, Insights, and Retention teams detect emerging customer problems, understand their root causes, prioritize issues, and track corrective action. Its Kyo AI Engine powers specialized agents for early warning, customer insight, and conversation quality analysis.

Business Problem Solved

Primary problem:

Companies collect large volumes of customer feedback and interaction data, but that information is often spread across separate support, survey, review, CRM, call, and social systems.

As a result, teams may identify customer problems only after contact volumes increase, CSAT falls, complaints accumulate, or customers begin to churn. Some clients and success stories – L’oreal, Holland&Barrett, Super.com, JustPark, Schuh, Gousto, Razorpay.

SentiSum brings these signals together and continuously analyzes them so teams can identify what is going wrong, why it is happening, which customers are affected, and which team should investigate the issue.

Additional problems addressed:

• Customer feedback is fragmented across different systems
• Root-cause analysis requires significant manual investigation
• CX insights can arrive too late for proactive action
• Manual ticket tagging produces inconsistent categories
• Product and Operations teams may lack direct access to customer feedback
• QA teams can only manually review a small sample of conversations
• Customer issues are difficult to prioritize by operational or commercial impact
• Emerging churn and dissatisfaction signals can remain hidden in unstructured conversations
• Human-agent and AI-agent conversation quality can be difficult to compare consistently

SentiSum also focuses on reducing avoidable contacts by identifying the underlying failures that generate repeated customer issues.

Key Services and Product Components

Unified Signals

SentiSum combines customer information from support platforms, call systems, surveys, reviews, social channels, CRM systems, and other feedback sources.

The same AI engine then analyzes these different sources using a consistent approach.

Business need: Create a shared view of customer problems instead of analyzing each feedback channel separately.

Kyo AI Engine

Kyo is the AI engine behind SentiSum’s CX intelligence capabilities.

Domain-trained AI engine, built over 10+ years of CX research, NLP innovation, and hands-on work with global brands

Multilingual: Kyo understands 100+ languages and pulls insights from tickets, chats, call transcripts, reviews, surveys, and CRM notes.. 

It analyzes customer data, identifies patterns and root causes, answers natural-language questions, and supports the platform’s specialized AI agents.

SentiSum states that Kyo is designed to base answers on customer data, provide supporting evidence, and flag uncertainty rather than fill unsupported gaps.

Early Warning Agent

The Early Warning Agent continuously monitors customer signals.

It looks for changes such as:

• Complaint spikes
• Sentiment changes
• Repeat contacts
• Resolution-time changes
• Product problems
• Payment failures
• Delivery issues
• Churn signals
• SLA risks

It then provides root-cause context and alerts teams through channels such as email, Slack, or Microsoft Teams. Brands using Early Warning Agent saw up to 40% fewer support escalations during peak periods.

Insights Agent

The Insights Agent allows teams to ask natural-language questions about customer experience data.

Examples include:

• Why did CSAT fall?
• What is driving refund requests?
• Which product issues generate repeat contacts?
• What changed in customer sentiment?
• What are the main churn risks?

Responses can include root causes, trends, supporting metrics, and customer conversations that support the analysis.

Quality Agent / Auto QA

The Quality Agent analyzes human and AI-agent conversations against quality criteria.

It supports:

• Conversation Quality Scores
• Predicted CSAT
• Agent quality analysis
• AI-agent quality analysis
• Issue-resolution assessment
• Coaching identification
• BPO performance comparison
• Transcript-level evidence
• Custom QA dimensions

SentiSum states that the Quality Agent can read 100% of conversations, no sampling “rather than relying on a small manually selected 2-5% QA sample”

Action Tracker

Teams can turn identified problems into assigned actions.

The Action Tracker supports ownership, status tracking, due dates, comments, and follow-up as teams work to resolve identified customer problems.

Customer Feedback Analytics

SentiSum analyzes unstructured feedback from calls, chats, emails, support conversations, reviews, surveys, and other customer channels.

It identifies topics, sentiment, contact reasons, and recurring issues so teams can understand what is driving customer experience outcomes.

Workflows Supported

Customer Experience → Voice of Customer → Customer Issue Analysis

Department: Customer Experience

Workflow: Voice of Customer

Specific process: Customer Signal Collection → AI Analysis → Issue Identification → Root-Cause Analysis → Prioritization → Business Action

SentiSum combines customer conversations and feedback, identifies recurring problems, and helps teams determine why they are occurring.

Customer Experience / Operations → Issue Monitoring → Early Warning

Department: CX / Operations

Workflow: Customer Experience Monitoring

Specific process: Incoming Customer Signals → Continuous Monitoring → Anomaly Detection → Root-Cause Analysis → Alert → Investigation

The Early Warning Agent monitors changes across customer signals and alerts teams when unusual patterns appear.

Product → Customer Feedback → Product Issue Prioritization

Department: Product

Workflow: Product Feedback

Specific process: Customer Feedback → Issue Detection → Root-Cause Analysis → Product Team → Prioritization

SentiSum identifies product bugs, UX blockers, feature problems, and other customer friction directly from customer conversations.

The Product team can use that evidence when deciding which problems require attention.

Customer Service → Quality Assurance → Conversation Review

Department: Customer Service / Quality Assurance

Workflow: Quality Assurance

Specific process: Customer Conversation → AI Quality Evaluation → Score / Issue Identification → QA Review → Coaching or Process Change

The Quality Agent evaluates both human-agent and AI-agent interactions using a shared QA framework.

Retention → Customer Risk Analysis → Intervention

Department: CX / Retention

Workflow: Customer Retention

Specific process: Customer Signals → Risk Detection → Root-Cause Analysis → Prioritization → Retention Action

SentiSum identifies patterns associated with frustration, repeat contacts, cancellation intent, and other customer-risk signals.

Department / User

Primary Departments

• Customer Experience
• Customer Service
• Customer Insights
• Operations

Primary Users

• CX leaders
• Customer Service leaders
• Customer Insights teams
• Customer Support managers
• Operations teams
• Quality Assurance teams
• Product managers
• Retention teams

Secondary Users

• Marketing teams
• Risk teams
• Leadership
• Executives
• AI / Automation teams

SentiSum states that the same customer intelligence can be tailored to Support, Product, Marketing, Operations, Risk, and Leadership users.

Decision-Maker / Buyer

 Primary buyer: Head of CX/Support 

However, its current product pages target CX, Product, Insights, Customer Care, Operations, and Retention leaders. These are the clearest supported stakeholders for evaluation and ownership.

Where SentiSum Sits in the Workflow

Workflow stage: Across the customer feedback and improvement workflow, with the main AI activity occurring during analysis, monitoring, and prioritization.

Position in the process:

Customer interacts with the company
→ conversation or feedback enters an existing support, CRM, survey, review, voice, or social system
→ SentiSum brings the customer signal into its intelligence layer
→ Kyo analyzes the content and identifies themes, sentiment, causes, risks, and anomalies
→ insights or alerts are delivered to the relevant team
→ the issue is prioritized and assigned
→ Product, Operations, Support, Risk, or another team investigates and implements a fix
→ the issue can be tracked through resolution

This makes SentiSum primarily an intelligence and decision-support layer between customer interaction data and the teams responsible for fixing the underlying problem.

AI Role

Analyze

Analyzes large volumes of structured and unstructured customer interaction data.

Classify

Identifies customer topics, contact reasons, issues, sentiment, and related categories.

Monitor

Continuously monitors incoming customer signals for changes.

Detect

Identifies anomalies, emerging complaints, product problems, sentiment shifts, repeat contacts, and other unusual patterns.

Search / Retrieve

Allows users to ask natural-language questions and retrieve relevant insights from customer interaction data.

Extract

Extracts entities, topics, customer issues, and other relevant information from conversations.

Recommend

Provides recommended actions based on identified issues and root causes.

Predict

The Quality Agent provides predicted CSAT for conversations that do not have survey responses.

This should be described specifically as predicted CSAT, rather than a broad predictive analytics capability.

Automate

Optional automation capabilities can route or resolve defined customer service workflows.

Assist Human Decision-Making

Provides evidence that CX, Product, Operations, QA, Retention, and leadership teams can use to decide what customer problems to address first.

Key Use Cases

Early Detection of Customer Problems

User: CX and Operations teams

Workflow: Customer Experience → Monitoring → Issue Detection

SentiSum monitors customer conversations, surveys, CRM information, and public feedback for unusual changes.

Business outcome: Helps teams identify emerging problems before they become larger complaint or support-volume issues.

Root-Cause Analysis

User: CX, Product, Insights, and Operations teams

Workflow: Customer Experience → Performance Analysis → Root Cause

Users can ask questions about changes in CSAT, complaints, refund requests, product issues, or repeat contacts.

Kyo analyzes supporting customer data to explain why the change occurred.

Business outcome: Reduces manual investigation and gives responsible teams evidence for deciding what to fix.

Unified Voice of Customer Analysis

User: Customer Insights and CX teams

Workflow: Voice of Customer → Feedback Consolidation → Analysis

SentiSum brings together support tickets, calls, surveys, reviews, CRM notes, social feedback, and other customer signals.

Business outcome: Creates a consistent customer view across teams and reduces dependence on separate channel-specific reports.

Product and Journey Improvement

User: Product and Operations teams

Workflow: Product → Customer Feedback → Issue Prioritization

SentiSum identifies product bugs, UX friction, service problems, and recurring customer complaints.

Business outcome: Helps Product and Operations teams prioritize improvements using customer interaction evidence.

Quality Assurance for Human and AI Agents

User: QA teams, Customer Service leaders, BPO managers

Workflow: Customer Service → Quality Assurance → Coaching / Improvement

The Quality Agent scores conversations, predicts CSAT, evaluates issue resolution, and links scores to underlying transcripts.

Business outcome: Expands QA coverage and helps teams identify specific coaching, process, BPO, or AI-agent quality problems.

Ideal For

SentiSum is relevant for organizations that:

• Handle high volumes of customer conversations
• Collect feedback across several channels
• Struggle to connect support, survey, CRM, review, and call data
• Need continuous detection of customer problems
• Want to understand why CSAT or other customer metrics change
• Need Voice of Customer insights for Product and Operations
• Want customer insights without relying on manual reporting for every question
• Need broader quality coverage across human and AI customer service interactions
• Want identified customer issues connected to ownership and corrective action

Business Outcomes

Faster Customer Issue Detection

Continuous monitoring helps teams identify emerging customer problems earlier.

Faster Root-Cause Analysis

AI analyzes customer evidence to help teams understand why customer experience metrics or contact patterns changed.

Reduced Avoidable Customer Contacts

Teams can identify the underlying process, product, delivery, billing, or experience failures that repeatedly generate customer contacts.

Improved Decision Support

Customer evidence becomes available to Product, Operations, CX, Marketing, Retention, Risk, and leadership teams.

Wider QA Coverage

The Quality Agent evaluates connected conversations rather than relying only on small manual samples.

Better Cross-Functional Accountability

Issues can be assigned to responsible teams and tracked through the Action Tracker.

Retention Support

Early-warning signals can help teams identify dissatisfaction and customer-risk patterns while there is still an opportunity to intervene.

Industries

SentiSum is designed to work across industries with significant customer interaction and feedback volumes.

Its website and customer examples show use in:

• Retail
• Ecommerce
• D2C / Subscription businesses
• Travel and Airlines
• SaaS / B2B Technology
• Food and Meal Delivery
• Mobility
• Financial Services / Fintech

Integrations

Customer Support and Conversation Platforms

• Zendesk
• Intercom
• Freshdesk
• Dixa
• Gorgias
• Salesforce
• Genesys
• Amazon Connect
• Five9
• Help Scout
• Gladly
• Sprinklr

Surveys and Reviews

• Qualtrics
• Medallia
• SurveyMonkey
• Typeform
• Trustpilot
• G2
• Google Reviews
• Apple App Store
• Google Play
• Reviews.io
• Yotpo
• Survicate
• Wootric

Social Channels

• Facebook
• Instagram
• WhatsApp
• TikTok
• YouTube
• X / Twitter
• Reddit

Data and CRM

• HubSpot
• Microsoft Fabric
• Snowflake

SentiSum states that it supports more than 100 systems. Where a native connection is unavailable, data can also be ingested through APIs, file transfer, or middleware.

Trust & Security

SentiSum states that it provides:

• SOC 2 Type II compliance
• GDPR compliance
• EU data residency
• Encryption at rest
• Encryption in transit
• Role-based access control
• Multi-factor authentication
• Regular penetration testing
• Customizable data retention
• PII redaction
• AWS infrastructure
• Data Processing Agreement availability