The complete intelligence platform for space-based solar power constellations. From energy optimization and market integration to collision avoidance, sustainability compliance, carbon avoidance reporting, and autonomous operations.
In 2026 the orbital energy economy stopped being theoretical. JAXA beamed the first solar power from orbit to the ground. Starcloud became a unicorn with the first GPU operational in space. SpaceX filed for a million data center satellites. The operators building this new infrastructure face a problem no single tool can solve today: coordinating energy generation, power beaming, compute workload, thermal limits, regulatory compliance and collision avoidance across thousands of heterogeneous spacecraft in real time.
Existing orbital tools were designed for telecom and earth observation constellations. None of them understand the coupling between power flow, GPU dissipation, phased-array steering and live traffic geometry. Operators still rely on generic FDS software, manual spreadsheets and custom scripts per analysis. KARDASHEV AI ships the first unified decision layer for this new asset class: a single platform that closes the loop between every physical system an orbital energy or compute operator has to juggle, from the first TLE download to the final regulatory filing.
Self-improving AI that coordinates entire constellations in real-time, balancing eight competing objectives with forward-looking trajectory evaluation. Learns from every optimization and every operational outcome.
High-precision targeting for microwave and laser power transmission. End-to-end link budget modeling with full atmospheric and ionospheric compensation.
Real-time space weather monitoring with predictive orbit corrections days before storm arrival. During severe storms, the AI automatically protects billions in hardware while maintaining partial energy delivery — continuous operation when competitors go offline.
Full-fidelity orbital simulation with SGP4 propagation and closed-loop feedback. Predictions validated against real operational outcomes. Simulate 10 years of constellation operations in minutes.
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.
Our optimization engine coordinates hundreds of satellites in real-time, adapting to failures and maximizing energy capture across the constellation.
Live telemetry from our optimization engine — monitoring space weather, element health, and energy delivery across the constellation.
Purpose-built for space-based solar power. Comprehensive orbital safety, sustainability compliance, autonomous operations, and a self-improving intelligence layer that gets smarter with every optimization.
Maximize energy capture and beam delivery to ground stations with intelligent resource allocation.
Track debris, coordinate sensor pointing, and feed collision warning systems in real time.
Every satellite guaranteed controlled deorbit. Fuel reservation, drag-assisted disposal, and role rotation ensure zero uncontrolled debris.
Automated SSR scoring integrated into the optimization loop. Every maneuver improves your sustainability rating.
Reentry trajectory optimization ensures complete satellite disintegration. Zero surviving fragments reaching the ground.
AI-prioritized debris removal targeting. Identifies which objects to remove first for maximum orbital safety impact.
Real-time conjunction screening with live data from multiple space surveillance networks. Automated risk classification, CCSDS-standard data exchange, and fuel-optimal evasive maneuvers from alert to execution.
Cross-constellation traffic coordination between multiple operators. The orbital equivalent of air traffic control.
Ready for ESA SOLARIS in-orbit demonstrators. Power budgets, beam test scheduling, and TRL assessment integrated.
Real-time access to the European Space Surveillance and Tracking network. Fragmentation analysis, re-entry monitoring, and cross-referencing with CelesTrak for the most complete orbital picture.
RF frequency allocation optimized to avoid interference with telecom, radar, and radio astronomy. ITU power density compliance.
AI-driven degradation prediction for panels, batteries, and thrusters. Proactive repositioning before component failure.
Demand-responsive beam allocation connected to terrestrial energy markets. Optimize revenue by directing power where real-time prices are highest.
Automatic constellation reconfiguration after satellite failures. Redistributes energy load and beam assignments without human intervention.
Automated verification against international space regulations. Real-time compliance monitoring for spectrum, debris, and deorbit timelines.
Multiple distribution strategies with fuel-aware automatic selection. Starts optimization from the configuration that minimizes lifetime station-keeping cost.
Computes orbital elements from raw angular and range observations. Full independence from external TLE providers.
Proactive multi-satellite maneuver optimization. Station-keeping, collision avoidance, and constellation phasing in a single unified schedule.
Optimizes satellite-to-ground-station communication windows for telemetry, commands, and energy transmission scheduling.
Complete power flow from solar irradiance through panel conversion, DC-RF, free-space loss, atmospheric attenuation, to watts delivered at the grid.
ML-based detection of anomalous satellite behavior across temperature, voltage, power, and attitude channels. Trend and correlation analysis.
Relocates satellites between regions based on real-time energy demand shifts. Seasonal optimization for hemisphere-aware power delivery.
Replays historical events with modifications. Simulates counterfactual storms, failures, and market shifts for risk assessment and insurance underwriting.
Predicts trajectories of small uncatalogued debris using learned correction factors. Detects and models fragmentation debris cloud evolution.
Resolves RF interference between SBSP operators sharing the same transmission frequencies. Time-sharing, frequency offset, and beam steering resolution.
Industry-standard SGP4/SDP4 propagation with automatic backend selection and upgrade path to higher-fidelity models.
Maps orbital shell congestion in real time. Identifies altitude bands approaching critical density thresholds and recommends proactive avoidance strategies.
Programmatic access to the full optimization pipeline. Upload constellations in OPM, OEM, TLE, or JSON, optimize, and export results for direct FDS integration.
Supports both microwave and laser power transmission. Computes link budgets, atmospheric losses, and receiver output for each wavelength. Recommends the optimal beam type for any mission.
Optimizes where to place ground receiving stations for maximum energy delivery. Considers cloud climatology, grid connectivity, electricity prices, and CO2 avoidance per site.
Quantifies CO2 avoided vs grid electricity using real IEA emission factors. Carbon payback period, EU ETS credit valuation, and comparison against terrestrial alternatives.
Energy management for orbital data centers. Optimizes power generation, battery state, and compute workload distribution across constellation nodes during eclipse transitions.
Turns the live compliance report into draft regulatory filings ready for legal review. Operators get an ITU-R Article 21 power-flux-density compliance statement, an ESA Zero Debris Charter compliance statement and an FCC Part 25 Schedule S summary in seconds, with a mandatory draft watermark on every page so the output cannot be confused with a final filing without an audit.
A focused link-budget tool for the orbital cellular operators that AST SpaceMobile, Lynk Global and Starlink DTC are commercialising. Computes path loss, Doppler shift and link margin for satellite-to-handset links across the four 3GPP NTN bands, so an operator can validate per-pass coverage on a real handset, IoT modem or broadband terminal in seconds.
A single STM dashboard for the entire orbital neighbourhood. Loads multiple operator constellations from public catalogues, surfaces the cross-operator close approaches, proposes coordination maneuvers between operators and maps traffic density per orbital shell — so a satellite operator can see and act on the traffic around their fleet from a single view.
Plans rendezvous and proximity operations for in-space servicing missions. Computes Δv budgets, burn sequences and relative trajectories so operators of refueling, inspection and debris-removal vehicles can size and schedule their next maneuver in seconds, on top of the same physics stack that powers the SBSP and orbital data centre tools.
Multi-layer orbital power grid with dedicated node roles. Routes energy LEO↔MEO↔GEO through retransmission and storage nodes, with hybrid generators contributing surplus back to the grid.
Joint optimisation of compute workload, satellite attitude and thermal cycle across multiple orbits ahead. Anticipates eclipse transitions and solar flux changes to maximise sustained utilisation while preventing GPU thermal violations.
The Optimal Power Flow router now reads per-node thermal headroom and scales every sink capacity accordingly. A data centre near its thermal limit automatically receives less power, so the grid never overloads a node that can't dissipate the heat — a closed-loop fusion of the power and thermal models that no other SBSP platform offers.
Space-mission grade confidence analysis. Runs dozens of perturbed replicas of the full orbital pipeline with TLE epoch drift, thermal mass variance, temperature noise and efficiency jitter, and reports p5/p50/p95 intervals on delivered power, thermal headroom and throttled sinks — the language aerospace engineers expect when sizing real constellations.
Every steered beam carries an automatic ITU-R Radio Regulations Article 21 power-flux-density compliance report. The platform computes the ground PFD from the effective EIRP and slant range, compares it against the applicable limit for the chosen frequency band, and returns a compliant flag with a decibel margin — so regulatory sign-off starts with the numbers, not a spreadsheet.
Spacecraft thermal model upgraded to publication-grade physics: Vallado conical penumbra eclipse, slew-rate constrained reaction-wheel attitude dynamics, ADCS power coupled into the heat budget, and a curated catalogue of real platform specs (Starcloud, JAXA OHISAMA, Google Suncatcher, Axiom ODC) with source-cited thermal mass fallbacks for undisclosed parameters.
Globally optimal energy routing across an orbital constellation. Filters every link by real geometric line-of-sight, then solves a min-cost max-flow over the full graph in a single pass — drawn from live public satellite catalogues and propagated to the planning instant with standard orbital mechanics.
Electronic beam steering with per-element phase control for the transmit array. Maximises received power density at the rectenna, suppresses sidelobes for ITU compliance, and reduces pointing error to fractions of a degree without mechanical actuators.
Every optimization run makes the platform smarter. Learned patterns persist across sessions, accumulating operational knowledge that improves recommendations over time.
Compares optimization predictions against real operational outcomes. Systematic errors automatically adjust priorities, creating a self-correcting intelligence layer.
Coordinates across multiple orbital layers simultaneously. Optimizes energy capture, relay routing, and collision avoidance between LEO, MEO, and GEO constellation layers.
Optimize orbital solar farms that beam clean energy to Earth 24/7, eliminating intermittency and maximizing yield per satellite.
Optimize power generation and delivery for any orbital asset — from satellite constellations to future space stations and in-orbit servicing platforms.
Dynamically redirect beam allocation across optimally placed ground receivers. The platform selects the best rectenna locations globally and routes energy based on real-time demand, pricing, and atmospheric conditions.
Solar relay satellites providing power during the 14-day lunar night. Collector arrays optimized for interplanetary mission propulsion.
Power management for the next generation of space-based compute infrastructure. Eclipse-aware workload scheduling, battery optimization, and energy routing for orbital GPU clusters.
HELIOS optimization benchmarks using real data from CelesTrak, NASA, NOAA, EU SST, ESA DISCOS, and ENTSO-E. Orbital trajectories validated with SGP4 propagation. Compared against static planning baselines.
HELIOS analyzes global orbital coverage and selects the optimal ground receiver locations. Each candidate scored on cloud climatology, grid emission factor, electricity price, and orbital visibility — then ranked to maximize energy delivery, revenue, and carbon avoidance.
We work with constellation operators, space agencies, and energy infrastructure developers. Whether you need optimization, sustainability compliance, carbon avoidance reporting, insurance assessment, or market integration — let's discuss your mission.