Constellation Intelligence Platform

The AI that
coordinates orbital
energy swarms

Real-time optimization for space-based solar power constellations. We coordinate thousands of satellites — maximizing energy capture, preventing collisions, and adapting to space weather.

Launch Simulator Read White Paper
10×
Solar intensity in orbit vs Earth
$1.3T
Space energy market by 2040
24/7
Continuous power generation
-94%
Collision events vs baseline

Thousands of satellites. Zero coordination software.

Space-based solar power requires constellations of thousands of satellites collecting energy and beaming it to Earth. The hardware is being built. But no software exists to coordinate these swarms in real time — deciding where each collector should orbit, how to orient its panels, and when to reconfigure.

A single collision between two satellites at orbital velocity generates debris that can cascade through the entire constellation. Without AI coordination, operators are flying blind — risking billions in hardware and years of development on static plans that can't adapt.

340 collisions = cascade failure

Four integrated systems.
One optimization platform.

01

Swarm Optimization Engine

Hierarchical multi-objective reinforcement learning (PPO) that decomposes constellations into orbital pods, reducing complexity from O(N²) to O(K² + K·M²). Enables real-time optimization for up to 10,000 elements.

02

Beam Precision AI

Sub-milliradian targeting for microwave and laser power transmission. End-to-end link budget modeling with atmospheric absorption, ionospheric scintillation, and Faraday rotation compensation.

03

Space Weather Engine

Real-time NOAA Kp-index integration for solar storm detection. Automatically reconfigures the constellation during geomagnetic events — protecting elements from radiation and compensating beam attenuation.

04

Digital Twin Simulator

Full-fidelity orbital simulation with SGP4/SDP4 propagation and J2-J6 perturbation corrections. Monte Carlo failure testing at 1%-30% rates. 500-satellite, 10-year simulations in under 4 minutes.

05

Cascade Avoidance System

Predictive collision modeling incorporating Kessler syndrome dynamics. Identifies and eliminates cascade-prone configurations before they become hazardous — even when individual collision probabilities are within tolerance.

// Live Demo

See the swarm think.

Our optimization engine coordinates hundreds of satellites in real-time, adapting to failures and maximizing energy capture across the constellation.

KARDASHEV.AI — SWARM OPTIMIZER v0.1 60 FPS

Powering the next era of civilization

Space-Based Solar Power

Optimize orbital solar farms that beam clean energy to Earth 24/7, eliminating intermittency and maximizing yield per satellite.

Orbital Compute Infrastructure

Coordinate power generation and distribution for space-based data centers. Ensure uninterrupted supply for AI compute workloads.

Directed Energy Delivery

Route orbital energy beams to remote installations or disaster zones on demand. Emergency power without ground infrastructure dependencies.

Lunar and Deep Space Operations

Solar relay satellites providing power during the 14-day lunar night. Collector arrays optimized for interplanetary mission propulsion.

Validated performance across reference configurations.

Results from controlled experiments in our digital twin environment. 500-satellite constellation at 550 km altitude, sun-synchronous orbit, compared against conventional planning baselines.

ENERGY CAPTURE
+54%
vs. uniform grid baseline
52.8% of theoretical maximum vs. 34.2% with static grid planning. Adaptive pod allocation maximizes solar exposure.
COLLISION AVOIDANCE
-94%
collision events over 10 years
3 events vs. 47 with grid baseline. Cascade-aware avoidance with Kessler syndrome modeling prevents chain reactions.
RESILIENCE
94%
output at 10% element failure
Maintains 81% output even at 25% failure rate. Monte Carlo validation across 10,000 failure scenarios.
FUEL EFFICIENCY
-43%
station-keeping ΔV per year
7.1 m/s vs. 12.4 m/s baseline. Optimized maneuver planning extends mission lifetime and reduces launch mass.
OPTIMIZATION TIME
<4 min
500-satellite full reconfiguration
Real-time capable on standard cloud GPU infrastructure. Hierarchical pod architecture enables linear scaling.
SCALE
10K
max constellation elements
Tested up to 10,000 elements in simulation. O(K² + K·M²) complexity enables real-time operation at scale.
// Get in touch

Ready to optimize your constellation.

We work with constellation operators, space agencies, and energy infrastructure developers. Reach out to discuss your mission requirements.

Contact Us Download White Paper ↓