KIRA: Kreate Intelligent Response Assistant

The Challenge

Problem Statement

The insurer's call centre was experienced, well-trained, and genuinely capable — but structurally limited in ways that were becoming harder to ignore. Customer expectations had changed dramatically. Policyholders expected immediate, intelligent support across channels and at any hour. But the insurer's support infrastructure remained tied to business hours, manual processes, and high-cost servicing models. The majority of customer queries were repetitive and operational. Policy status checks, payment confirmations, renewal queries, and claim references still required human intervention. At the same time, critical customer moments like FNOL reporting often happened outside support hours, creating frustration during emotionally stressful situations. Previous chatbot pilots had already failed because they relied on rigid decision trees, static FAQs, and disconnected escalation workflows — making customer experiences worse instead of better. The insurer needed something fundamentally diff erent, not another chatbot, but an intelligent insurance support platform capable of understanding context, emotion, urgency, and continuity.

Key Issues Involved

Incidents and claims reporting did not follow business hours
High operational cost for handling repetitive customer queries
Skilled agents spending time on low-value servicing interactions
Existing chatbot systems unable to understand natural conversations
Static FAQ systems disconnected from live policy data
Customers forced to repeat information during escalations
Lack of multilingual conversational support
Renewal strategies disconnected from actual customer experience history

Notable Impact

Delayed FNOL reporting and slower claims initiation
Growing customer frustration during emergency situations
Trust defi cits caused by after-hours service gaps
Ineffi cient call centre resource utilization
Inconsistent claims intake quality
Weak personalization in renewal engagement
Missed retention opportunities among at-risk policyholders

Our Solution

Kreate Technologies approached the problem differently.

Instead of building another FAQ chatbot, KIRA was designed around the emotional reality of insurance conversations. A customer casually checking their renewal date on a Sunday afternoon is not in the same state of mind as a customer standing beside a damaged vehicle at 2 AM.

KIRA was built to understand that difference.

The platform combines insurance-trained LLM intelligence, multilingual NLP, live policy integrations, sentiment detection, renewal intelligence, and omnichannel continuity into a single AI-powered conversational ecosystem. The goal was not simply to automate conversations — but to resolve issues, reduce friction, and improve trust throughout the policyholder journey.

Key Solution Components

Conversational Journeys

KIRA treats every interaction as part of a broader customer journey rather than a single transaction. It recognises context, conversation history, emotional tone, and policyholder behaviour across the lifecycle.

LLM Intelligence, Insurance-Tuned

The platform was fi ne-tuned using the insurer’s product catalogue, policy language, exclusion clauses, and real call centre transcripts, enabling KIRA to understand how policyholders actually speak, not just how policies are written.

True Omnichannel Presence

WhatsApp, mobile app, web chat, and IVR all operate through one conversational engine with shared policy data and conversation continuity. Customers never have to restart conversations when switching channels.

FNOL Intake with Distress-First Design

KIRA guides customers through claims reporting one step at a time with calm, structured conversations designed specifi cally for stressful situations. Supporting documents are collected directly within the conversation fl ow and pushed into claims systems automatically.

Real-Time Policy Intelligence

Live API integrations allow KIRA to answer policy-specifi c questions in real time instead of relying on static FAQ responses.

Proactive Renewal Intelligence

A machine learning propensity model evaluates policyholder behaviour, claims history, engagement patterns, and sentiment trajectory 60 days before policy expiry to personalise renewal communication strategies.

Agent Assist with Warm Handoffs

When escalation is required, human agents receive a complete contextual briefi ng including conversation summary, policy status, issue category, sentiment score, and recommended opening responses, allowing conversations to continue instead of restart.

Secure and Compliant Architecture

The platform includes OTP and biometric authentication, end-to-end encryption, JWT session tokens, PII masking, and IRDAI-compliant data handling practices.

Implementation Phases:

Five Phases from Insight to Impact

KIRA was not deployed in a single go-live. Each phase was validated before the next began — ensuring that every capability was built on a foundation that actually worked in the real world.

Journey Mapping & Conversational Design

Policyholder journey mapping across claims, servicing, and renewals. Emotional-context conversational workflow design and identification of high-frequency customer interaction patterns.

AI Model Fine-Tuning

LLM training using insurance documents and real customer conversations. NLP development for multilingual understanding, intent detection, and insurance-specific entity extraction.

Omnichannel Deployment

WhatsApp, mobile app, web chat, and IVR integration with real-time policy administration and claims system connectivity. Secure authentication and live policy intelligence implementation.

Renewal Intelligence & Agent Assist

ML-based renewal propensity engine deployment, personalised outreach workflows for different customer segments, and warm escalation and Agent Assist capabilities rollout.

AMC & Continuous Learning

Continuous retraining using agent-corrected interactions, quarterly recalibration of renewal prediction models, and ongoing monitoring of CSAT, NPS, and service performance metrics.

Journey Mapping & Conversational Design

Policyholder journey mapping across claims, servicing, and renewals. Emotional-context conversational workflow design and identification of high-frequency customer interaction patterns.

AI Model Fine-Tuning

LLM training using insurance documents and real customer conversations. NLP development for multilingual understanding, intent detection, and insurance-specific entity extraction.

Omnichannel Deployment

WhatsApp, mobile app, web chat, and IVR integration with real-time policy administration and claims system connectivity. Secure authentication and live policy intelligence implementation.

Renewal Intelligence & Agent Assist

ML-based renewal propensity engine deployment, personalised outreach workflows for different customer segments, and warm escalation and Agent Assist capabilities rollout.

AMC & Continuous Learning

Continuous retraining using agent-corrected interactions, quarterly recalibration of renewal prediction models, and ongoing monitoring of CSAT, NPS, and service performance metrics.

Journey Mapping & Conversational Design

Policyholder journey mapping across claims, servicing, and renewals. Emotional-context conversational workflow design and identification of high-frequency customer interaction patterns.

AI Model Fine-Tuning

LLM training using insurance documents and real customer conversations. NLP development for multilingual understanding, intent detection, and insurance-specific entity extraction.

Omnichannel Deployment

WhatsApp, mobile app, web chat, and IVR integration with real-time policy administration and claims system connectivity. Secure authentication and live policy intelligence implementation.

Renewal Intelligence & Agent Assist

ML-based renewal propensity engine deployment, personalised outreach workflows for different customer segments, and warm escalation and Agent Assist capabilities rollout.

AMC & Continuous Learning

Continuous retraining using agent-corrected interactions, quarterly recalibration of renewal prediction models, and ongoing monitoring of CSAT, NPS, and service performance metrics.

Results

Business Outcomes

24×7 service availability across WhatsApp, mobile app, web chat, and IVR
68% of routine servicing interactions resolved by KIRA without human intervention
40% reduction in escalation handling time through structured Agent Assist context briefings
30% improvement in FNOL completion rates with distress-first conversational intake design
22% renewal uplift among at-risk policyholders through ML-driven personalised outreach
Claims teams received pre-structured FNOL records with sentiment scoring before each morning shift

Operational Impact

The call centre evolved — agents shifted from repetitive servicing queries to high-value, emotionally complex customer interactions
Policyholders no longer needed to repeat information when conversations moved from AI to human support
Better claims readiness — FNOL records arrived pre-structured with incident classification and supporting documents
Stronger customer trust built through consistent availability, multilingual support, and contextual continuity
Renewal performance improved because service interactions throughout the year now informed retention strategies
A foundation now exists for extending KIRA's intelligence into fraud detection, cross-sell, and claims settlement workflows

Key Takeaways

The call centre evolved — agents shifted from repetitive servicing queries to high-value, emotionally complex customer interactions
Policyholders no longer needed to repeat information when conversations moved from AI to human support
Better claims readiness — FNOL records arrived pre-structured with incident classification and supporting documents
Stronger customer trust built through consistent availability, multilingual support, and contextual continuity
Renewal performance improved because service interactions throughout the year now informed retention strategies
A foundation now exists for extending KIRA's intelligence into fraud detection, cross-sell, and claims settlement workflows

KIRA: Kreate Intelligent Response Assistant

About the Project

The Challenge

Problem Statement

Key Issues Involved

Notable Impact

Our Solution

Key Solution Components

Conversational Journeys

LLM Intelligence, Insurance-Tuned

True Omnichannel Presence

FNOL Intake with Distress-First Design

Real-Time Policy Intelligence

Proactive Renewal Intelligence

Agent Assist with Warm Handoffs

Secure and Compliant Architecture

Implementation Phases:

Journey Mapping & Conversational Design

AI Model Fine-Tuning

Omnichannel Deployment

Renewal Intelligence & Agent Assist

AMC & Continuous Learning

Journey Mapping & Conversational Design

AI Model Fine-Tuning

Omnichannel Deployment

Renewal Intelligence & Agent Assist

AMC & Continuous Learning

Journey Mapping & Conversational Design

AI Model Fine-Tuning

Omnichannel Deployment

Renewal Intelligence & Agent Assist

AMC & Continuous Learning

Results

Business Outcomes

Operational Impact

Key Takeaways