CoverForge.com

AI deployment optimizer that maximizes coverage from limited MANPADS inventory

Score: 6.8/10MAHard Build
Brand Colors

The Opportunity

Problem

Moroccan army previously lacked sufficient MANPADS to counter low-flying drones, helicopters, and cruise missiles

Solution

CoverForge analyzes terrain, threat corridors, population centers, and your exact MANPADS count to recommend optimal firing positions. It runs thousands of simulations to show coverage overlap and kill probability, allowing commanders to protect far more area with the same limited number of systems than intuitive placement would achieve.

Target Audience

Moroccan military air defense commanders and North African defense strategists

Differentiator

The only geospatial optimization tool purpose-built for MANPADS using PostGIS terrain analysis calibrated on North African elevation and vegetation data.

Brand Voice

professional

Features

Interactive Coverage Map

must-have50h

Mapbox-based interface showing terrain, threats, and coverage cones

Genetic Algorithm Optimizer

must-have85h

Calculates best deployment locations for given inventory

Threat Vector Library

must-have30h

Common low-altitude approach paths for drones and missiles in the region

Inventory Integration

must-have25h

Input current MANPADS count and model variants

Coverage Heatmap Generator

must-have40h

Visual probability of intercept across entire area of responsibility

Simulation Runner

must-have60h

Monte Carlo simulation of hundreds of attack scenarios

Exportable Deployment Plans

nice-to-have25h

PDF and KMZ files for field use

Historical Threat Overlays

nice-to-have30h

Past incident data layers from regional conflicts

Multi-Unit Coordination

nice-to-have35h

Plan deployments across allied units with shared visibility

Total Build Time: 380 hours

Database Schema

organizations

ColumnTypeNullable
iduuidNo
nametextNo
countrytextNo
created_attimestampNo

users

ColumnTypeNullable
iduuidNo
organization_iduuidNo
roletextNo
emailtextNo

Relationships:

  • organization_id -> organizations.id

deployments

ColumnTypeNullable
iduuidNo
organization_iduuidNo
nametextNo
aor_geojsontextNo
manpads_countintNo
coverage_scoreintYes
created_attimestampNo

Relationships:

  • organization_id -> organizations.id

positions

ColumnTypeNullable
iduuidNo
deployment_iduuidNo
latitudetextNo
longitudetextNo
elevationintYes
kill_probabilityintYes

Relationships:

  • deployment_id -> deployments.id

API Endpoints

POST
/api/optimize

Run deployment optimization algorithm

🔒 Auth Required
GET
/api/deployments

List user's deployment plans

🔒 Auth Required
POST
/api/terrain

Upload custom terrain elevation data

🔒 Auth Required
GET
/api/coverage

Return heatmap data for a deployment

🔒 Auth Required

Tech Stack

Frontend
Remix + TailwindCSS + Mapbox GL
Backend
Ruby on Rails
Database
PostgreSQL with PostGIS
Auth
Auth0
Payments
Flutterwave
Hosting
Fly.io
Additional Tools
Python microservice (PuLP + genetic algorithm)Redis

Build Timeline

Week 1: Map foundation and auth

45h
  • Remix app with Mapbox
  • Auth0 integration
  • Basic organization system

Week 2: Geospatial data layer

50h
  • PostGIS schema
  • Terrain import pipeline
  • Basic map controls

Week 3: Optimization engine

70h
  • Python genetic algorithm service
  • API integration
  • Basic scoring

Week 4: Visualization and simulation

55h
  • Coverage heatmap renderer
  • Monte Carlo simulation UI
  • Position markers

Week 5: Inventory and reporting

45h
  • Inventory manager
  • PDF/KMZ export
  • Comparison tools

Week 6: Polish and payments

35h
  • Flutterwave integration
  • Mobile responsive fixes
  • Documentation
Total Timeline: 6 weeks • 320 hours

Pricing Tiers

Starter

$0/mo

3 plans per month

  • Single area plans
  • Basic optimization
  • Limited simulations

Professional

$35/mo

Unlimited

  • Unlimited plans
  • Full threat library
  • Advanced algorithms
  • Heatmaps
  • Exports

Command

$119/mo

Unlimited

  • All Professional features
  • Multi-unit collaboration
  • Historical data layers
  • Priority computation
  • Dedicated support

Revenue Projections

MonthUsersConversionMRRARR
Month 13514%$171$2,052
Month 631018%$1,953$23,436

Unit Economics

$110
CAC
$1150
LTV
3.5%
Churn
79%
Margin
LTV:CAC Ratio: 10.5xExcellent!

Landing Page Copy

Get More Protection From Every MANPADS You Own

AI geospatial optimization that shows exactly where to place your limited systems for maximum coverage against low-flying threats.

Feature Highlights

North African terrain optimized
Genetic algorithm recommendations
Coverage probability heatmaps
Instant scenario testing
Field-ready export formats

Social Proof (Placeholders)

"'We increased theoretical coverage by 43% using CoverForge recommendations.' — Moroccan Air Defense Planner"
"'This should be standard issue for every battalion commander.' — Tunisian Strategist"

First Three Customers

Begin with outreach to planning staff at the Moroccan Royal Armed Forces Air Defense Command using warm intros from defense industry contacts. Offer free Professional tier access for 60 days to two planning departments. Present findings at the next North African Defense Conference to generate additional leads from Algeria and Mauritania.

Launch Channels

LinkedIn (defense planning titles)African Armed Forces forumsGeo-spatial intelligence communitiesDirect outreach to air defense planning directorates

SEO Keywords

manpads deployment optimizationair defense positioning softwareoptimal manpads placementmilitary coverage heatmapgeospatial defense planningmanpads positioning ai

Competitive Analysis

ESRI Defense Solutions

esri.com
Enterprise licensing
Strength

Powerful GIS platform

Weakness

Generic, requires GIS expertise and expensive add-ons

Our Advantage

Purpose-built MANPADS optimizer with one-click recommendations

Palantir Gotham

palantir.com
Multi-million contracts
Strength

Extremely powerful data integration

Weakness

Overkill and inaccessible for most North African forces

Our Advantage

Focused, affordable, and fast for this specific use case

🏰 Moat Strategy

Continuous feedback loop from deployed plans vs actual outcomes will refine the optimization algorithms into a proprietary North African defense model.

⏰ Why Now?

Recent conflicts demonstrate that intuitive MANPADS placement leaves massive coverage gaps. Newer drone threats require mathematically optimal positioning that commanders currently lack tools to calculate.

Risks & Mitigation

technicalhigh severity

Optimization algorithm produces unrealistic positions

Mitigation

Constrain solutions with military doctrine rules and validate with advisors

marketmedium severity

Commanders distrust black-box AI recommendations

Mitigation

Provide full transparency into scoring methodology and allow manual overrides

legalmedium severity

Use of satellite/terrain data may have restrictions

Mitigation

Only use publicly available elevation data (SRTM, OpenTopography)

Validation Roadmap

pre-build21 days

Validate optimizer logic with 5 retired air defense officers

Success: All 5 agree recommendations are superior to manual planning

mvp45 days

Pilot with planning staff from one Moroccan brigade

Success: They adopt at least one generated plan for exercise

Pivot Options

  • Expand to full IADS (Integrated Air Defense System) planning
  • Offer as consulting service with on-site workshops
  • License algorithm to larger defense primes

Quick Stats

Build Time
320h
Target MRR (6 mo)
$4,200
Market Size
$18.5M
Features
9
Database Tables
4
API Endpoints
4