Earth observation filtering
Identify useful frames before downlinking full sensor captures.
Orbital edge AI runtime
Deploy AI to the edge of space.
belto lets satellite operators run AI models onboard constrained orbital hardware, turning raw sensor data into compact mission-ready insights before downlink.
Problem
Orbital systems collect more data than they can efficiently move.
Satellites operate under hard constraints: limited bandwidth, intermittent downlink, power budgets, memory limits, and mission-critical timing.
01
Massive sensor data
Earth observation, telemetry, and onboard sensors can produce more raw data than operators can downlink quickly.
02
Limited downlink
Connectivity windows are constrained, intermittent, and expensive to use for raw data that may not be mission-relevant.
03
Delayed processing
Cloud-first workflows force teams to wait until data reaches the ground before extracting operational insight.
Solution
Process onboard. Downlink what matters.
belto packages models, rules, and mission constraints into deployable jobs that can run on constrained edge systems.
Onboard
Run AI workflows close to the sensor, before raw data leaves the spacecraft or remote system.
Compact
Transmit structured alerts, detections, summaries, and prioritized outputs instead of unnecessary raw data.
Bounded
Define jobs around mission constraints for bandwidth, latency, power, memory, and operating context.
Workflow
A clean mission pipeline from model to insight.
01
Deploy model
Package model artifacts with rules, thresholds, and mission constraints.
02
Process onboard
Run inference and logic against sensor or telemetry streams near the source.
03
Compress output
Reduce raw signals into compact, structured mission outputs.
04
Transmit insight
Prioritize detections, alerts, and summaries for downlink.
Use cases
AI workflows for constrained orbital and remote environments.
belto is designed for workflows where insight is more valuable than raw volume.
Wildfire detection
Flag likely wildfire signatures for faster operational awareness.
Vessel detection
Prioritize maritime detections and regions of interest.
Telemetry anomaly detection
Surface unusual signals from onboard telemetry streams.
Predictive threat alerts
Detect patterns that may indicate operational risk.
Autonomous downlink prioritization
Choose what should be transmitted first during narrow windows.
Degraded communications
Keep AI workflows useful when links are limited or intermittent.
Product
An SDK/runtime for mission-constrained AI deployment.
belto packages models, rules, and mission constraints into deployment jobs optimized for bandwidth, latency, power, and memory.
Mission package builder
Bundle AI models, preprocessing rules, thresholds, metadata, and mission limits into a single deployable package.
Runtime simulation
Test expected behavior against constrained compute, memory, latency, and bandwidth assumptions before deployment.
Mission logs
Inspect what ran, what was detected, what was compressed, and what would be transmitted.
Demo
Simulate a mission package before the real screenshot lands.
Login to the belto demo to deploy an AI package to a simulated satellite and inspect mission logs.
Research
Technical grounding for orbital edge AI.
Read the belto research record for additional context on the technical direction behind the platform.
Contact
Testing AI workflows for satellites or remote infrastructure?
belto is built for teams exploring onboard intelligence, constrained inference, and mission-ready edge AI workflows.