An automation layer for satellite scheduling at scale

Automate how capture schedules are generated, optimised and maintained. Working across single satellites, full constellations or multiple constellations operating together.

A single system for optimised capture planning

Replace labour-intensive scheduling workflows with automated optimisation.

Multi-asset scheduling

Schedule a single satellite, an entire constellation, or multiple constellations through one system.

High-fidelity satellite modelling

Evaluate requests against orbital mechanics, flight dynamics, and sensor constraints.

ML-driven optimisation

Generate optimised daily capture schedules in seconds rather than hours.

Conflict resolution

Automatically resolve tasking conflicts and capacity trade-offs.

Continuous ingestion of requests

Evaluate incoming orders and tasking requests in real time.

Increased asset utilisation

Maximise performance across satellites and sensors.

How it works in practice

Turn manual planning into automated optimisation.

Ingest

Incoming customer orders and tasking requests are continuously ingested into the scheduling system.

Model

Each request is evaluated against high-fidelity digital models of satellites, including orbital mechanics, flight dynamics, and sensor constraints.

Optimise

Arlula’s ML scheduling system generates an optimised daily capture schedule in seconds.

Resolve

Conflicts and capacity trade-offs are automatically resolved without manual analysis.

Built with your requirements in mind

✓ Enterprise grade security
✓ Audit ready by design
✓ API first architecture
✓ Modular by design
✓ Vendor neutral infrastructure
✓ Public or private cloud
✓ Standards based interoperability
✓ Granular access control
✓ Licensing aware
✓ Enterprise grade security
✓ Audit ready by design
✓ API first architecture
✓ Modular by design
✓ Vendor neutral infrastructure
✓ Public or private cloud
✓ Standards based interoperability
✓ Granular access control
✓ Licensing aware

Built for scaling constellations

Manual scheduling workflows break first when constellations grow, tasking demand increases, or response time becomes critical.

Constellation Orchestration replaces labour-intensive planning with automated optimisation, enabling you to scale from early missions to complex multi-constellation operations without expanding scheduling teams.

Faster tasking response

Generate optimised schedules in seconds.

Higher utilisation

Increase capture performance across satellites and sensors.

Reduced operating costs

Minimise manual scheduling effort.

Scalable growth

Support increasing customer demand without increasing headcount.

Live and maintained in weeks, not months

Adopt automated scheduling without rebuilding mission systems.

Build it yourself

Average 12  months

Month 0–3

Develop internal scheduling logic for one satellite.

Month 3–6

Expand planning across additional assets.

Month 6–12+

Implement cross-constellation optimisation and constraint handling.
Develop priority logic, conflict resolution, and real-time re-tasking across assets.

Ongoing Maintenance

Maintain manual optimisation and conflict resolution processes.

High internal cost. Long time to value. Permanent operational burden.

With Constellation Orchestration

Average 4 weeks

Week 0-4

Deploy automated scheduling layer.

Live with Light Maintenance

Operate through AI-driven optimisation.

Week 4+

Scale across constellation assets.

Live in weeks. No internal build. No long-term maintenance load.

Let’s talk about how you run EO today

Most conversations start with understanding your current systems, workflows and constraints to see how Arlula can empower your team.