OCOrbitChip

OrbitChip · Space-grade silicon

AI inference chips built for orbit.

OrbitChip helps spacecraft run reliable onboard intelligence across radiation, power, thermal, and mission constraints. Choose the compute profile that survives the orbit you are actually flying.

Radiation-tolerant inference · Fault-aware scheduling · Mission spec sheets

Radiation toleranceHigh
Power envelope≤ 24W
Thermal ratingModerate bus
Inference118 TOPS est.
Orbit classGEO reference
Mission durationMulti-year

The space compute problem

Terrestrial AI silicon assumes fresh air, cheap power, and a technician around the corner. None of that survives launch.

Radiation breaks conventional electronics

Single-event effects and cumulative dose are not theoretical failure modes — they are weekly telemetry for any serious bus.

Downlink is expensive

Megabits per minute are a recurring operational tax. Onboard inference shifts decisions to where photons are already paid for.

Onboard autonomy is rising

Docking, proximity ops, and closed-loop science require deterministic latency budgets terrestrial clouds cannot meet.

Power budgets are tight

Every watt competes with propulsion, thermal rejection, and payload duty cycles. Compute must declare an envelope, not a wish.

Thermal windows are narrow

Eclipse transitions and hot-case payloads squeeze margins. Inference scheduling must be thermally aware, not opportunistic.

Mission failure is expensive

Insurance lines and launch slots do not forgive silent data corruption in autonomy loops.

Mission Chip Configurator

The same UI your team uses in flight reviews: orbit class, duration, payload, sensor path, power budget, thermal constraint, radiation exposure, inference workload, and autonomy level — mapped to silicon, fit score, and a mission spec sheet.

Open interactive demo

Constraint panels

Orbit
Duration
Payload
Sensor
Power
Thermal
Radiation
Workload
Autonomy

Outputs

  • — Recommended chip profile & class
  • — Mission fit score & radiation index
  • — Power envelope & thermal risk matrix
  • — Redundancy recommendation
  • — Exportable mission spec sheet

Mission environments

LEO

Constellation-scale inference with frequent ground contact but hostile SEU rates in certain shells.

GEO

Long dwell, high-value services — radiation accumulation and thermal stability dominate qualification.

Lunar

Cislunar logistics and surface robotics — extended autonomy with intermittent ground visibility.

Deep space

Heliocentric and outer-planet trajectories — maximum TID/SEE exposure and repair-by-wire constraints.

Orbital robotics

Proximity ops and servicing — real-time perception fused with low-latency control.

Technical advantage

Radiation-tolerant architecture

Memory scrub, ECC paths, and hardened MAC arrays sized for your orbit class — not a consumer die in a shield can.

Low-power inference

TOPS-per-watt envelopes that respect spacecraft bus budgets from rideshare to flagship GEO.

Fault-aware compute

Checkpoint policies and dual-rail execution modes aligned to your autonomy certification story.

Thermal-aware scheduling

Duty-cycle shaping that coordinates with radiator capacity instead of fighting it.

Mission-specific profiles

Die variants and firmware lanes tuned for EO, robotics, relay, or science payloads.

Mission compute dashboard

Fit score, radiation gauge, power envelope, thermal margin, inference throughput, redundancy guidance, and spec sheet preview — tuned from your last configuration.

Full dashboard →

Mission compute dashboard

Live view of fit score, radiation index, power envelope, and thermal margin. Configure on the demo to push a new profile here — values persist locally until refreshed.

Open configurator

Recommended silicon

OC-X2 Stratospheric-Power Edge AI

X2 — high-throughput GEO / MEO

Mission fit

87

Radiation readiness

High

84

Model index / qualification envelope

Power envelope

18W

Steady-state inference estimate

Ceiling 24W

Headroom 6W

Idle / safe-modePeak duty

Orbit environment

GEO — geosynchronous. Hostile particle flux scaled for Medium environment over 6 months — 2 years.

Payload processing

Earth observation with Optical / multispectral — sustained 118 TOPS-class envelope at ~44 ms median frame latency (mission estimate).

Thermal margin

25%

Power headroom vs declared bus ceiling

Thermal risk: Moderate

Risk matrix

  • low

    Total ionizing dose (TID) margin

    Readiness High (84/100 model index).

  • medium

    Single-event upset (SEU) exposure

    GEO trajectory class.

  • medium

    Thermal coupling / dissipation

    Moderate — 25% power headroom.

  • low

    Inference duty cycle vs downlink

    Supervised autonomy — workload Detect & track.

Inference throughput

118

TOPS INT8-equivalent envelope

Median latency

44 ms

Mission spec sheet

ORBITCHIP · CONFIDENTIAL
Mission fit87/100
Radiation readinessHigh
Power draw (est.)18W
Thermal riskModerate
Inference latency44ms
RedundancyDual module recommended

Who we build with

Satellite operatorsSpace robotics teamsDefense contractorsLunar infrastructure companiesResearch missions

Why now

More spacecraft are flying with less margin for ground-in-the-loop decisions. Payloads generate more bits per second than downlink budgets can carry. Autonomy stacks are moving from slide decks to flight software — and they need silicon that respects radiation physics, not marketing TOPS.

Engagement models

Not per-seat SaaS. Flight hardware programs are scoped like silicon — review, kit, flight qualification, partnership.

Mission Review

Fixed-scope architecture sprint

  • Radiation & thermal assumptions
  • Compute lane diagram
  • Risk register draft

Prototype Kit

Lab bring-up package

  • Reference carrier + BSP
  • Rad-test coupon plan
  • Inference benchmarks

Flight Program

Qualification-aligned delivery

  • Environmental matrix
  • Lot traceability
  • On-orbit telemetry playbook

Strategic Partner

Multi-mission roadmap

  • Silicon roadmap co-design
  • Dedicated applications team
  • ITAR-aware workflows

FAQ

Is this a generic AI accelerator?
No. OrbitChip targets inference under explicit radiation, thermal, and power envelopes — the same variables flight software teams already track.
Do you replace our flight computer?
Typically no. OrbitChip sits as a dedicated inference tile alongside your avionics stack, with deterministic interfaces into your autonomy software.
How are estimates generated?
The demo engine applies local heuristics mapping orbit class, duration, payload, sensor path, power budget, and autonomy level into a silicon recommendation and risk matrix. No paid APIs.

Design the compute before the mission fails.

Run the Mission Chip Configurator, push results to your mission dashboard, and bring the spec sheet into your next program review.