Insurance use case

Quote & Pricing Agent AI Agent

Automate quote generation and pricing guidance across Web chat, WhatsApp while improving quote turnaround time and reducing drop-offs.

Example: Quote & Pricing Agent that generates quotes, compares riders, and nudges follow-ups.

Channels: Web chat · WhatsApp Outcomes: Faster quote turnaround · improved conversion
Enterprise security
Prebuilt integrations
Go-live in weeks
Omnichannel
Teams

Claims Ops, Policy Servicing, Renewals Ops, CX

Entry points

Website widget · Inbound number · WhatsApp deep link · Email · Agent/broker portal

Deployment

Secure actions, supervised handoff, and full audit trails.

Who it's for

Built for teams that need speed and control

Claims Ops Policy Servicing Renewals Ops CX Web chat WhatsApp Website widget Inbound number WhatsApp deep link Email Agent/broker portal
What it does

Outcomes-first jobs your buyers care about

Generate quote

How: Captures demographics and coverage requirements.

Outcome: Faster quote delivery

Compare riders

How: Explains optional riders and pricing impact.

Outcome: Higher conversion

Follow-up nudges

How: Schedules reminders and shares saved quotes.

Outcome: Lower drop-offs

Route high-intent

How: Connects to advisors for complex needs.

Outcome: Better close rates

End-to-end workflow

Step-by-step flow buyers expect to see

  1. 1

    Trigger: quote request

    Customer asks for pricing.

  2. 2

    Data capture

    Age, sum assured, riders.

  3. 3

    Quote

    Generate premium options.

  4. 4

    Action

    Send quote and payment link.

  5. 5

    Exceptions

    Medical underwriting flags.

  6. 6

    Wrap-up

    Saved quote + follow-up.

Sample conversations

Real scenarios with clear resolution paths

Scenario A: Happy path: term quote Web chat

Customer: Need a 1Cr term plan.

Agent: For age 32, premium starts at 8,200/year.

Customer: Send the quote.

CRM note: 1Cr term quote sent. Age 32.
Scenario B: Edge case: rider confusion WhatsApp

Customer: What is critical illness cover?

Agent: It adds coverage for listed conditions. Adds ~900/year.

CRM note: Critical illness rider explained.
Scenario C: Escalation: medical underwriting Voice

Agent: This needs medical underwriting. I will schedule a call.

CRM note: Medical underwriting required. Advisor callback scheduled.
Integrations

Systems connected with secure actions

Systems of record

Policy admin, Claims system, CRM, TPA

Service stack

Zendesk, Freshdesk, Knowledge base

Comms

Dialer/telephony, WhatsApp provider, SMS, Email

Action tools

Document collection, eSign, Payment links, Survey tools, Quote engine, Advisor scheduling

Supported methods: API · Webhooks · RPA fallback Data sync: Read + write
Guardrails & controls

Enterprise readiness built in

Role-based access with OTP or SSO for sensitive actions
PII redaction and masked views for IDs and payment details
Policy-locked response blocks for compliance language
Sentiment and risk thresholds that trigger human takeover
Full transcripts, action logs, and disposition codes
QA sampling, scorecards, and prompt/version control
KPIs & measurement

What you will improve

FNOL completeness

Claims initiated with full documentation.

Claim cycle time

Time from FNOL to settlement.

Renewal rate

Policies renewed before lapse.

Lapse rate

Policies not renewed within grace.

AHT

Average handling time per interaction.

CSAT

Customer satisfaction post-servicing.

Complaint rate

Escalations per 1,000 policies.

Agent productivity

Cases handled per FTE.

Configuration

Flexible to your policies, tone, and tools

Intents and flows
Tone and brand voice
Knowledge sources (FAQs, SOPs, policy docs)
Eligibility and routing rules
Dispositions and tags
Languages and accents (voice)
Business hours, SLAs, and fallback policies
Implementation plan

A phased rollout with clear deliverables

Week 0

Discovery + call listening

  • Workflow map and intent list
  • SOP alignment and compliance notes
  • Success metrics and QA plan
Phase 1

Pilot on 1 channel + 1 workflow

  • Agent prompts and guardrails
  • Test cases and failover scripts
  • Live dashboard with baseline KPIs
Phase 2

Expand intents + integrate systems

  • System actions and data sync
  • Multi-channel coverage
  • Supervisor playbooks
Phase 3

Optimize + scale

  • Continuous QA coaching
  • A/B tested prompts and flows
  • Governance and reporting
FAQs

Buyer objections, answered

How do you handle exceptions?

The agent routes exceptions to a human with full context, suggested next steps, and a clear disposition.

What happens when the agent is unsure?

It asks clarifying questions, consults the approved knowledge base, or escalates based on confidence thresholds.

Can we restrict what it can say or do?

Yes. Guardrails lock sensitive responses and require approvals for authenticated actions.

How are transcripts stored?

Transcripts and action logs are stored with retention controls and audit access.

How does handoff work with our CRM or ticketing?

The agent writes structured notes, tags, and next steps directly into your system of record.

What languages and accents are supported for voice?

Major Indian and global languages with configurable voice and accent options.

See this agent live on your workflow

See the agent live with your data, policies, and channels.

Deploy an AI-supervised agent for your highest-volume workflow.

We consult, design, build, and manage the agent end-to-end.