Orbital Logistics Infrastructure

INTERMODAL SPACE

The intermodal container system for Earth orbit.

Smart endpoints, lean containers. We're building permanent orbital infrastructure that moves cargo at commodity cost — not the price of a throwaway vehicle per shipment.

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The Problem

Every kilogram moved in orbit rides a throwaway vehicle.

The launch industry solved reusability on the ground. But once a payload reaches orbit, the logistics model reverts to 1960s economics.

$45,000/kg

Dragon cargo cost per kilogram. Every box pays for the vehicle that moves it.

Single-use

Each in-space tug flies once, for one customer, on one mission. Bespoke and disposable.

Monthly

Best-case cadence. No FedEx in orbit. No conveyor belt. Every delivery is a custom mission.

As commercial stations from Vast, Axiom, and Orbital Reef come online, this bottleneck becomes the binding constraint on the orbital economy.

The Thesis

Smart endpoints, lean containers.

Concentrate intelligence in permanent platforms. Keep the cargo container cheap, standardized, and dumb.

HUBCATCHReleaseContainerCapture
1

Permanent platforms

A Hub computes and ejects. A Catcher maneuvers and captures. Both are reusable capital assets, amortized over thousands of cycles.

2

Lean containers

Only a beacon, a small solar array, and minimal trim propulsion. Cheap, standardized, rides rideshare launches to LEO.

3

Commodity cost

Per-shipment cost collapses to amortized capital. Customers pay commodity launch price once. Everything after is shared infrastructure.

The analog:Malcolm McLean's shipping container revolution. He didn't build a better ship — he built a better box and redesigned the port to match.

The System

Three elements. One architecture.

Two smart platforms handle all guidance, computation, and capture. The container between them is lean by design.

HUBreleaseCONTAINERcaptureCATCHER
H1

RELEASE PLATFORM

HUB-1 MERIDIAN

~300 kg

  • Piezo-tuned spring release cradle
  • 0.5 mm/s Δv repeatability
  • 12-container capacity, 2 kW solar
C1

LEAN CONTAINER

CARRIER-1 PALLET

~50 kg dry / 155 kg wet

  • S-band beacon at 1 Hz
  • 50 W solar array, 15 W draw
  • Cold-gas trim (~0.3 m/s Δv)
A1

CAPTURE PLATFORM

CATCHER-1 APEX

~400 kg dry

  • 5 m glide rail, 3 m capture funnel
  • Eddy-current magnetic brake
  • Three-point latch, 2.5 kW peak

Operations

How it works.

Six steps from launch to cargo transfer. No dedicated vehicle. No throwaway propulsion.

STEP 01

Rideshare Launch

Container rides a commodity rideshare to LEO. Standard ESPA Grande envelope. No dedicated vehicle.

STEP 02

Hub Release

Hub ejects the container with a 5.87 m/s prograde pulse. Impulse logged to 0.5 mm/s accuracy.

STEP 03

Ballistic Coast

Container coasts for 94.6 minutes on a closed Hill ellipse. S-band beacon broadcasts position at 1 Hz.

STEP 04

Terminal Correction

Container fires cold-gas thrusters for ~2 seconds. Catcher does 90% of the guidance work.

STEP 05

Capture

Container enters the glide rail at ~5 cm/s. Magnetic brake absorbs Δv. Mechanical latch locks it in.

STEP 06

Service & Re-dispatch

Container is reloaded and re-dispatched. Endpoints are permanent. One Hub serves many Catchers.

By the Numbers

Validated by simulation.

Every claim is backed by a reproducible Monte Carlo trajectory simulation.

5.87 m/s

Prograde Δv for transfer

100 km co-orbital at 500 km

94.6 min

Transit time

One Hub orbital period

36 m

3σ miss distance

Inside 40 m capture aperture

99.9%

Capture rate

10,000 Monte Carlo trials

< $5K/kg

Target shipment cost

vs. $45K/kg Dragon

$50K

Pre-seed SAFE

$6M cap, 20% discount

Competitive Landscape

Different architectural quadrant.

Competitors fly one customer per flight with active propulsion. We build permanent infrastructure plus cheap, standardized containers.

ApproachCost / kg
Dragon cargo~$45,000
In-space tug$10K–30K
Intermodal Space$2K–5K

The analog isn't another space company— it's Malcolm McLean, who didn't build a better ship. He built a better box and redesigned the port to match.

The Founder

Building from first principles.

MO

Michael E. Onofre

Founder & CEO

Arizona State University. Applied AI operator background with self-taught orbital mechanics. Author of the white paper, Monte Carlo trajectory simulation, and full subsystem architecture.

Every technical claim is reproducible — the trajectory notebook runs end-to-end in Jupyter and regenerates every figure.

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