AI InfrastructureFire & Contents Restoration

How we saved a fire restoration company 3 full-time employees and 30 days per project

A Southern California fire content restoration company was drowning in manual item research. We built a custom AI system that turned a month-long process into a same-day workflow.

Built in 2 weeks
3 FTEs → 1 FTE
30+ days → hours

3 → 1

Full-time employees

Now only QA

30+ → 1

Days per project

Same-day delivery

10,000+

Items per house

Fully automated

2-3 wks

Time to build

Discovery to deploy

The Problem

Thousands of items. Manual research. Months of work.

When a home is damaged by fire, a contents restoration company is brought in to catalog every item in the house — furniture, electronics, appliances, clothing, kitchenware, everything. Each item needs to be individually researched to find its current retail replacement price so the insurance company can properly reimburse the homeowner.

For this SoCal-based company, a single house could contain anywhere from 2,000 to 10,000+ items. Every one of those items had to be entered into a spreadsheet, manually researched online to find the best current price, and then verified for accuracy. On top of that, the correct local tax percentage had to be calculated for each item based on the client's specific city or jurisdiction.

This process required 3 full-time employees working exclusively on item research and verification. Even with a dedicated team, each client project took over a month to complete. The manual nature of the work meant errors were common, consistency was difficult to maintain, and scaling to take on more clients was nearly impossible.

3 full-time employees dedicated to manual research

1+ month turnaround per client project

2,000-10,000+ items researched by hand per house

No standardized tax calculation across jurisdictions

Inconsistent pricing sources and verification

Unable to scale to take on more clients

Our Process

From discovery to deployment in 2 weeks.

01

Discovery & Workflow Mapping

Week 1

We spent the first week embedded in their process — understanding how items were cataloged, how pricing was researched, how spreadsheets were structured, and where the bottlenecks lived. We mapped every step from intake to insurance submission.

02

AI System Architecture

Week 1-2

We designed a custom AI pipeline that could ingest item lists, research pricing across major retailers (Target, Amazon, Home Depot, Walmart), calculate location-based tax, and output verified results with confidence scoring and source URLs.

03

Build & Integration

Week 2-3

We built the system, integrated it with their existing workflow, and added smart flagging for items over or under $500 that needed human verification. The tax calculation module was calibrated to pull accurate rates by city and jurisdiction.

04

Testing & Deployment

Week 3

We ran the system against real historical projects to validate accuracy, refined the confidence scoring thresholds, and deployed to production. Their team was trained on the QA workflow in a single session.

The Solution

A custom AI system that does the work of 3 people.

We built a custom AI pipeline that automates the entire contents pricing and verification workflow — from item identification to price research, tax calculation, and quality flagging.

Automated Price Research

The AI researches and verifies pricing for every single item in a fire-damaged home. It searches across major retailers — Target, Amazon, Home Depot, Walmart — and returns the actual retail price along with the source URL for full transparency.

Location-Based Tax Calculation

A custom tax percentage module that automatically identifies the correct tax code based on the client's city or area. No more manual lookups or guesswork — every item gets the accurate local tax rate applied automatically.

Confidence Scoring

Every item match receives a confidence score from the AI. High-confidence matches sail through automatically, while lower-confidence items are flagged for human review. The team knows exactly where to focus their attention.

Smart Flagging System

Items priced under or over $500 are automatically highlighted for priority QA verification. This ensures high-value items get the extra scrutiny they need while low-risk items are processed efficiently.

Before & After

The transformation at a glance.

Before

After Vantier

Employees Required

3 full-time

1 (QA only)

Turnaround Per Client

30+ days

Hours

Items Per House

Manual research

AI-processed

Tax Calculation

Manual lookup

Automated by location

Price Verification

Spreadsheet-based

URL-sourced with confidence scores

Quality Assurance

Spot-checking

Smart flagging ($500+ items)

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