QualiScan

AI-powered visual inspection for flawless custom parts in low-volume production.

Score: 5.6/10SOMedium Build
Brand Colors

The Opportunity

Problem

Small-scale manufacturers struggle with inconsistent quality control for custom parts when scaling from prototypes to production runs.

Solution

QualiScan lets manufacturers upload photos of custom parts, where AI instantly detects defects like cracks, misalignments, and surface issues. It generates reports with pass/fail scores and improvement recommendations, ensuring consistent quality as you scale from prototypes to runs. Simple mobile app integration makes QC checks routine on the shop floor.

Target Audience

Owners and engineers in small-scale manufacturing shops producing custom parts with low-volume runs

Differentiator

Tailored AI models pre-trained on custom machined parts data, achieving 95% accuracy without custom training per shop.

Brand Voice

professional

Features

Photo Upload & AI Scan

must-have20h

Upload part photos via web or mobile; AI analyzes for defects in seconds.

Defect Detection Report

must-have15h

Instant PDF reports with images, scores, and annotations.

Batch Processing

must-have12h

Scan multiple parts in one upload for production runs.

Historical Trends

must-have18h

Dashboard showing defect rates over time per part type.

Mobile App QC

must-have25h

Native-like mobile capture with real-time feedback.

Custom Defect Library

nice-to-have10h

Add shop-specific defects for AI fine-tuning.

Integration with CAD

nice-to-have15h

Overlay AI results on CAD models.

Alert Notifications

nice-to-have8h

Email/SMS for high defect rates.

Total Build Time: 123 hours

Database Schema

users

ColumnTypeNullable
iduuidNo
emailtextNo
shop_nametextNo

parts

ColumnTypeNullable
iduuidNo
user_iduuidNo
nametextNo
descriptiontextYes

Relationships:

  • user_id references users(id)

inspections

ColumnTypeNullable
iduuidNo
part_iduuidNo
image_urltextNo
ai_scoreintNo
defects_detectedtextYes
created_attimestampNo

Relationships:

  • part_id references parts(id)

defect_types

ColumnTypeNullable
iduuidNo
user_iduuidNo
nametextNo

Relationships:

  • user_id references users(id)

API Endpoints

POST
/api/inspections

Create new inspection with photo upload

🔒 Auth Required
GET
/api/inspections/:id

Get single inspection report

🔒 Auth Required
GET
/api/parts

List user's parts

🔒 Auth Required
POST
/api/parts

Create new part

🔒 Auth Required
GET
/api/dashboard/trends

Get defect trends data

🔒 Auth Required
POST
/api/defect_types

Add custom defect

🔒 Auth Required

Tech Stack

Frontend
Next.js 14 + Tailwind + shadcn/ui
Backend
Next.js API routes
Database
Supabase Postgres
Auth
Supabase Auth
Payments
Stripe
Hosting
Vercel
Additional Tools
Vercel AI SDK for inspectionsSupabase Storage

Build Timeline

Week 1: Core auth and user setup

40h
  • User signup/login
  • Basic dashboard

Week 2: AI inspection MVP

40h
  • Photo upload
  • AI integration & reports

Week 3: Parts & trends

35h
  • Parts CRUD
  • Trends dashboard

Week 4: Polish & payments

30h
  • Mobile responsive
  • Stripe integration
  • Landing page

Week 5: Nice-to-haves

20h
  • Custom defects
  • Notifications
Total Timeline: 5 weeks • 200 hours

Pricing Tiers

Free

$0/mo

No trends, watermarked reports

  • 5 scans/month
  • Basic reports

Pro

$32/mo

1 shop user

  • Unlimited scans
  • Trends dashboard
  • PDF exports
  • Mobile app

Enterprise

$99/mo

5 shop users

  • All Pro + teams
  • Custom AI tuning
  • API access
  • Priority support

Revenue Projections

MonthUsersConversionMRRARR
Month 11003%$100$1,200
Month 66008%$1,500$18,000

Unit Economics

$25
CAC
$400
LTV
4%
Churn
88%
Margin
LTV:CAC Ratio: 16.0xExcellent!

Landing Page Copy

Catch Every Defect Before It Ships

AI visual inspection tailored for custom parts – scale production without quality dips.

Feature Highlights

Instant AI defect detection
Shop floor mobile checks
Trend insights for improvement
Seamless from prototype to production

Social Proof (Placeholders)

"'Saved us 20% rework!' – Joe, Machinist"
"'Game-changer for low-volume runs.' – Sarah, Shop Owner"

First Three Customers

Post in r/manufacturing and r/CNC about free beta access for first 10 shops; email 50 targeted LinkedIn engineers from small shops in US/EU; offer free Pro tier for 3 months in exchange for feedback and case studies.

Launch Channels

Product Huntr/manufacturingr/SaaSHacker NewsLinkedIn Manufacturing groups

SEO Keywords

custom parts quality controlAI part inspection softwaremanufacturing defect detectionlow volume QC toolCNC quality assurance

Competitive Analysis

Cognex VisionPro

cognex.com
Hardware $5k+
Strength

High accuracy industrial

Weakness

Expensive hardware, no SaaS

Our Advantage

Affordable camera-based SaaS, no setup

🏰 Moat Strategy

Proprietary dataset of custom part defects grows with user uploads, improving AI exclusively.

⏰ Why Now?

Cheap AI vision APIs + rise in custom/low-volume manufacturing via Etsy/Shopify makers scaling up.

Risks & Mitigation

technicalmedium severity

AI accuracy varies by part material

Mitigation

Start with common metals, user feedback loop

markethigh severity

Shops prefer manual QC

Mitigation

Free tier demos value

executionlow severity

Image storage costs

Mitigation

Supabase optimized storage

Validation Roadmap

pre-build7 days

Interview 10 shop owners on pain

Success: 5 confirm willingness to pay $32

mvp30 days

Build core scan, get 20 beta users

Success: 80% retention week 2

launch7 days

PH launch, track signups

Success: 100 users week 1

growth30 days

SEO content + emails

Success: 10% MoM growth

Pivot Options

  • Expand to assembly line inspection
  • B2B white-label for larger factories
  • General product photo QA for ecom

Quick Stats

Build Time
200h
Target MRR (6 mo)
$1,500
Market Size
$500.0M
Features
8
Database Tables
4
API Endpoints
6