๐Ÿค– AI-FIRST INSURANCE PLATFORM

Artificial Intelligence Built for Indian Insurance Brokers

Not a gimmick. Not a chatbot add-on. Six real AI workflows that save time, recover revenue, and grow your brokerage โ€” built into the platform from day one.

Book a Live AI Demo โ†’ Why Our AI is Different
6
AI Modules
Claude AI
Powered By
Real-Time
Predictions
0
Manual Triggers

AI Renewal Prediction Engine

Stop losing 25% of your policy book every year. Our machine learning model scores each policy for renewal probability based on dozens of signals โ€” and tells your team exactly which renewals need human attention.

How it works

  • Model analyses payment history, claim frequency, agent engagement, policy tenure, and product type
  • Outputs a risk score per policy (High / Medium / Low) refreshed daily
  • Auto-segments your renewal book โ€” high-risk to top agents, low-risk to auto-reminder workflow
  • Multi-channel reminder sequence: WhatsApp, SMS, email, agent call
  • Tracks outcomes and continuously improves model accuracy
Business Impact: Brokers using AI renewal prediction typically see 8โ€“15% improvement in renewal rates. For a โ‚น5 Cr premium book, that's โ‚น30+ Lakh in retained revenue annually.
โšก RENEWAL RISK DASHBOARD
OLV/HLT/2026/847293HIGH RISK
Rajesh Patel ยท Family Floater ยท โ‚น84,500 ยท Risk: 87%
OLV/MTR/2026/293847WATCH
Mehta Industries ยท Commercial Vehicle ยท โ‚น1,24,000 ยท Risk: 54%
OLV/TRV/2026/412847LOW RISK
Sharma Family ยท Travel ยท โ‚น6,200 ยท Risk: 12%
Sample dashboard โ€” actual data per brokerage

Fraud Detection & Commission Anomaly Alerts

Most brokers lose 3โ€“5% of brokerage revenue to undetected fraud and reconciliation errors. Our anomaly detection model catches the patterns humans miss โ€” agent fraud, ghost policies, commission mismatches, duplicate submissions.

What it catches

  • Agents with statistically abnormal conversion rates (possible fake submissions)
  • Same customer phone/address submitted by multiple agents
  • Policies cancelled within 30 days of issuance โ€” commission claw-back required
  • Insurer credit notes that don't match expected commission
  • TDS deducted at wrong rates due to PAN mismatch
  • Unusual claim patterns (clustering, timing, geography)
Business Impact: Recovers 3โ€“5% of brokerage revenue typically lost to undetected fraud and reconciliation errors. For a โ‚น1 Cr brokerage business, that's โ‚น3โ€“5 Lakh annually.
๐Ÿšจ FRAUD ALERTS ยท TODAY
Commission Mismatch Detected
ICICI Lombard credit note โ‚น1.2L short vs calculated. Agent Code: AG-247. Period: Oct 2026.
Duplicate Customer Pattern
Same mobile +91-987X-XX-X234 submitted by 3 agents in last 7 days. Review recommended.
Abnormal Conversion Rate
Agent VK-12: conversion 3.4ร— team average. Investigation flag raised.
Sample alerts โ€” actual data per brokerage

Smart Cross-Sell Recommendation Engine

Every customer is a multi-product opportunity. A customer with only motor insurance is statistically likely to need health. A family with health but no term life is exposed. Our AI continuously identifies these gaps and recommends the right product to the right agent at the right time.

How it works

  • Analyses each customer's existing portfolio across all product lines
  • Identifies gap products based on profile (age, family size, occupation, income)
  • Computes "next best offer" probability using comparable customer outcomes
  • Surfaces recommendations on the agent's mobile app as actionable leads
  • Timing-aware: surfaces health recommendation when motor renewal is approaching
Business Impact: Increases per-customer revenue 20โ€“35%. Cross-sells have 3x higher conversion than cold outreach because the agent already has a relationship.
๐Ÿ’ก AGENT'S MOBILE RECOMMENDATIONS
Patel Family ยท Existing: Family Health
Suggested: Term Life โ‚น1Cr ยท 78% likely to buy
Reason: Sole earner, age 38, 2 children. Health renewal next month โ€” call together.
Mehta Exports ยท Existing: Marine Open Cover
Suggested: Group Health for 24 employees ยท 65% likely
Reason: Mentioned hiring in last meeting. Competitor quoting them โ€” act fast.
Sharma ยท Existing: Two-Wheeler
Suggested: Personal Accident ยท 54% likely
Reason: Daily commuter. Low cost. High win probability.

AI Customer & Agent Chatbot

A customer at 9pm asks if their health policy covers daycare procedures. Your office is closed. They call a competitor instead. Our AI chatbot โ€” deployed on WhatsApp โ€” handles 60โ€“70% of routine queries automatically, escalating only when needed.

What the chatbot handles

  • For customers: Policy status, expiry date, coverage queries, claim status, premium payment, document requests
  • For agents: Product info, premium calculation guidance, claim procedure, commission queries
  • Renewal nudge bot: Proactive WhatsApp outreach 60/30/15/7 days before renewal
  • Languages: English, Hindi (Gujarati, Tamil, Marathi available on request)
  • Smart escalation to human agent when intent is complex or buying signal detected
Business Impact: Customer support cost down 40โ€“60%. Response time from hours to seconds. Customer satisfaction (CSAT) typically improves 20+ points.
๐Ÿค–
InsureFlow Assistant
online
Hi! I noticed your motor policy renews in 7 days. Premium is โ‚น8,420 (same as last year). Pay now?
Does it cover the new bumper?
Yes โ€” your zero-dep cover includes plastic and rubber parts. Bumper damage is covered.
Ok send payment link
Sent โœ“ UPI ยท Cards ยท NetBanking

Intelligent Document Classification

Customers upload Aadhaar, PAN, RC, policy PDFs. Traditionally an agent then types all the data manually โ€” slow, error-prone, expensive. Our document AI reads the upload, classifies the document type, extracts every field, and pre-fills the data automatically.

What it processes

  • KYC documents โ€” Aadhaar, PAN, Passport, Voter ID, Driving Licence
  • Vehicle documents โ€” RC, insurance policy, PUC certificate
  • Health documents โ€” past policy schedule, claim documents, medical reports
  • Marine documents โ€” invoice, packing list, bill of lading
  • Auto-validates against IRDAI KYC norms and CKYC registry
  • Flags missing or expired documents with actionable next steps
Business Impact: Reduces customer onboarding time from 45 minutes to under 5 minutes. Eliminates 90%+ of manual data entry errors. Frees up agent time for selling.
๐Ÿ“„
Document uploaded
aadhaar_rajesh_patel.jpg
AI EXTRACTED โœ“
Type: Aadhaar Card
Name: Rajesh Hiralal Patel
DOB: 12-Mar-1985
UID: XXXX XXXX 4729
Address: 7, Saurabh Society, Ahmedabad
CKYC verified โœ“

Predictive Business Intelligence & Commission Reconciliation

Most brokers cannot tell you, at any given moment, exactly what they are owed by insurers and what they owe to agents. Our AI continuously reconciles insurer credit notes against expected commission and flags every rupee of mismatch โ€” before payout, not after.

What it monitors

  • Line-by-line comparison of insurer credit note vs calculated commission
  • TDS deduction validation per agent's PAN status and cumulative annual payments
  • Slab tier upgrades โ€” alert when an agent crosses threshold
  • Policy cancellation impact on commission claw-back
  • Predictive cash flow โ€” forecasts next month's commission inflow with confidence intervals
  • Agent performance trend alerts โ€” top performers, declining performers
Business Impact: Eliminates 3โ€“5% commission leakage. Agent disputes drop sharply when commission is transparently calculated and verifiable.
๐Ÿ“Š COMMISSION RECONCILIATION ยท OCT 2026
Expected from ICICI Lombardโ‚น12,84,400
Received in credit noteโ‚น11,62,800
Variance flaggedโˆ’โ‚น1,21,600 (9.5%)
AI Investigation: 14 policies in batch had revised slab rate due to insurer commission norm update effective 01-Oct. Suggested: raise dispute with insurer attaching policy IDs and original commission schedule.
Sample reconciliation โ€” actual data per brokerage
How InsureFlow AI is Different

Most "AI in insurance" is marketing language. Here's how real, working AI compares to manual processes and surface-level chatbots.

CapabilityManual / ExcelBasic ChatbotInsureFlow AI
Renewal at-risk identificationReminder to everyoneRule-based dates onlyML model with 80%+ accuracy
Fraud detectionCatch after the lossNot supportedReal-time anomaly alerts
Commission reconciliationManual Excel checkNot supportedLine-by-line auto-match
Customer queries 24/7Office hours onlyFAQ-only chatbotPersonalised, policy-aware
Cross-sell intelligenceAgent's memoryNot supportedPortfolio-aware recommendations
Document data entryType each fieldNot supportedAuto-extract & validate
Continuous learningNoStatic rulesModel improves with your data
India-specific tuningManual workaroundsGeneric global modelIRDAI rules + Indian insurers
AI features โ€” common questions
What AI technology powers InsureFlow?โ–ผ
InsureFlow uses Claude AI from Anthropic combined with custom machine learning models trained on insurance broking data. AI models are continuously updated based on your brokerage's actual data, so accuracy improves over time.
How accurate is the renewal prediction model?โ–ผ
After 6 months of training on a brokerage's renewal data, the model typically achieves 80โ€“90% accuracy in identifying at-risk policies. Brokers using AI renewal prediction report 8โ€“15% improvement in overall renewal rate.
Is the AI chatbot available in regional languages?โ–ผ
The chatbot supports English and Hindi out of the box, with Gujarati, Tamil, Marathi, and Bengali available on request. Voice and text both supported via WhatsApp Business API.
How is InsureFlow AI different from generic AI tools?โ–ผ
InsureFlow AI is trained specifically on Indian insurance broking workflows, IRDAI compliance rules, and product catalogues. Unlike generic AI, it understands policy structures, commission rules, claim TAT requirements, and Indian regulatory context.
Do brokers need data scientists to use AI features?โ–ผ
No. All AI features work out of the box. The system automatically trains on your data and presents results in the dashboards your team already uses. No machine learning expertise required โ€” your agents and operations team use the AI without ever knowing it's AI.