PolicyMapper

Visual data transformer for insurtech legacy schemas.

Score: 7.6/10UKMedium BuildReady to Spawn
Brand Colors

The Opportunity

Problem

Enterprise insurtech teams suffer massive delays and ballooning costs integrating modern tech stacks into legacy insurance systems.

Solution

PolicyMapper lets teams visually map and transform complex insurance data from legacy formats to JSON/GraphQL without code. It handles ACORD XML, policy hierarchies, and validation rules automatically. Deploy as serverless functions to cut integration costs by 70% and time from weeks to hours.

Target Audience

Enterprise teams in insurtech companies

Differentiator

AI-assisted mapping suggestions trained on 10k+ insurance schemas for 90% auto-match accuracy.

Brand Voice

supportive

Features

Schema Visualizer

must-have18h

Upload legacy schema, see interactive graph of fields/relations.

Drag-Drop Mapper

must-have22h

Link legacy fields to modern outputs with type coercion.

AI Auto-Mapper

must-have25h

One-click suggest mappings using insurance ML model.

Transformer Playground

must-have15h

Test mappings live with sample data.

Export Functions

must-have12h

Generate Next.js/Supabase-ready serverless code.

Version Control

nice-to-have10h

Git-like history for mappings.

Batch Validation

nice-to-have8h

Run schema validations on bulk data.

Team Collaboration

future20h

Share and comment on mappings.

Total Build Time: 130 hours

Database Schema

users

ColumnTypeNullable
iduuidNo
emailtextNo

Relationships:

  • belongs to teams

teams

ColumnTypeNullable
iduuidNo
nametextNo

Relationships:

  • has many users, has many mappings

mappings

ColumnTypeNullable
iduuidNo
team_iduuidNo
nametextNo
legacy_schemajsonbNo
mappings_datajsonbNo
created_attimestampNo

Relationships:

  • foreign key team_id -> teams.id

tests

ColumnTypeNullable
iduuidNo
mapping_iduuidNo
input_datajsonbNo
outputjsonbYes
passedboolNo

Relationships:

  • foreign key mapping_id -> mappings.id

API Endpoints

GET
/api/mappings

List mappings

🔒 Auth Required
POST
/api/mappings

Create mapping with schema

🔒 Auth Required
POST
/api/mappings/:id/auto-map

Run AI auto-map

🔒 Auth Required
POST
/api/mappings/:id/test

Run test

🔒 Auth Required
GET
/api/mappings/:id/export

Download code

🔒 Auth Required

Tech Stack

Frontend
Next.js 14 + Tailwind + React Flow
Backend
Next.js API + Supabase
Database
Supabase Postgres
Auth
Supabase Auth
Payments
Stripe
Hosting
Vercel
Additional Tools
Vercel AI SDK for mapping ML

Build Timeline

Week 1: Setup and schema viz

25h
  • Auth/DB
  • Schema upload/visualizer

Week 2: Mapping editor

30h
  • Drag-drop UI
  • Basic mapper logic

Week 3: AI and testing

28h
  • AI integration
  • Playground/tests

Week 4: Exports and payments

20h
  • Code gen
  • Stripe
  • Dashboard

Week 5: Polish

15h
  • Versioning
  • Landing
Total Timeline: 5 weeks • 118 hours

Pricing Tiers

Free

$0/mo

No exports

  • 3 mappings
  • Basic AI

Pro

$29/mo

50 tests/mo

  • Unlimited mappings
  • Full AI
  • Exports

Enterprise

$199/mo

Unlimited

  • Collaboration
  • Custom AI fine-tune

Revenue Projections

MonthUsersConversionMRRARR
Month 11515%$65$780
Month 612020%$580$6,960

Unit Economics

$60
CAC
$1800
LTV
4%
Churn
88%
Margin
LTV:CAC Ratio: 30.0xExcellent!

Landing Page Copy

Map Legacy Insurance Data Visually – No Code

AI-powered transformers to modern in hours.

Feature Highlights

AI-powered suggestions
Live testing
One-click code export
ACORD/XML specialist
Team sharing

Social Proof (Placeholders)

"'90% auto-mapped our policy DB' – Eng Lead, NextInsure"

First Three Customers

Run targeted LinkedIn ads to 'insurtech engineer' titles with free schema upload tool; share demo video in Insurtech Twitter spaces; email 100 from insurtech job boards offering beta access.

Launch Channels

Product Huntr/insurtechTwitter #insurtechIndie Hackers

SEO Keywords

insurtech data mappingACORD XML transformerlegacy policy schema converterinsurance data integration tool

Competitive Analysis

Custom enterprise
Strength

ETL power

Weakness

No visual AI for insurance

Our Advantage

Insurtech-focused, instant exports, affordable

🏰 Moat Strategy

ML models trained on insurance data, improving with user mappings for network effects.

⏰ Why Now?

Rise of composable insurtech stacks needing quick data portability post-2023 rate hikes.

Risks & Mitigation

technicalmedium severity

AI mapping accuracy dips on rare schemas

Mitigation

Fallback manual + user feedback loop

Validation Roadmap

pre-build5 days

Validate with 5 schema samples from forums

Success: 80% auto-match

Pivot Options

  • General ETL visualizer
  • Health data mapper
  • API schema tool

Quick Stats

Build Time
118h
Target MRR (6 mo)
$800
Market Size
$300.0M
Features
8
Database Tables
4
API Endpoints
5