Should you build or buy Space Situational Awareness & Conjunction Assessment (Collision Avoidance) Software?

Space Situational Awareness & Conjunction Assessment (Collision Avoidance) Software screens a satellite's predicted trajectory against a catalog of tracked objects, computes collision probabilities, and generates avoidance maneuver recommendations when risk thresholds are crossed. Operators use it to protect fleet assets, meet regulatory safety obligations, and maintain orbital slots in an increasingly congested environment.

Copy reviewed 2026-10-04 · Research revision 2026-09-29

Sources: spacex.com; digitalcommons.usu.edu; space-track.org; github.com

Separate the screening data from the analytics. Basic screening is free: the U.S. Space Force provides conjunction data messages through Space-Track at no cost, and NASA publishes its collision-probability tools as open source. Planet and SpaceX both run their own collision-avoidance software in production on top of outside screening. What still favors buying is high-accuracy commercial tracking from sensor operators like LeoLabs and Slingshot Aerospace, plus the staff to run the process. Decide whether your constraint is the analytics and automation or the quality of the tracking data, and buy what you can't assemble.

Build it, buy it, or bridge?

⚒ Build it
✓ Buy it
➔ Bridge
Cost shape
Free Space-Track CDMs and NASA's open probability code cover the basics; better tracking costs extra
Cloud-native SaaS conjunction services are far cheaper than replicating data-backed catalogs
Custom conjunction analytics and maneuver logic consuming a provider's observation data via API
Time to value
Screening data is available on day one; validation and staffing take longer than the code
SaaS providers deliver screening alerts and probability estimates against live catalogs immediately
Quick baseline protection; custom automation and thresholds built incrementally
Differentiation captured
Custom probability thresholds, maneuver generation tuned to propulsion constraints, proprietary workflow integration
Collision avoidance is a shared safety function, not a competitive differentiator
Autonomous maneuver generation on top of a data-rich provider relationship
AI feasibility today
Planet and SpaceX run self-built collision avoidance in production; SpaceX's runs onboard
Established providers bundle AI analytics with proprietary observation data; hard to separate
Custom AI models trained on provider-supplied catalog data and telemetry feeds
Who it fits
Operators with flight-dynamics staff who want their own thresholds and maneuver automation
Operators without flight-dynamics staff, or those needing high-accuracy commercial tracking
Large constellations wanting automated maneuver generation on top of a commercial data subscription

When building makes sense

The build case is real, and it's documented. Planet built its own maneuver automation for its SkySat fleet: planned maneuvers go to Space-Track, and the conjunction data messages that come back are checked against Planet's own miss-distance and collision-probability thresholds. SpaceX puts an onboard autonomous collision-avoidance system on every Starlink satellite, fed by screening from LeoLabs and the U.S. Space Force. The inputs are open to any operator. The U.S. Space Force provides close-approach notifications and CDMs through Space-Track at no cost, and NASA's CARA team publishes its collision-probability tools as open source. A custom layer makes the most sense when you need thresholds calibrated to your fleet's maneuver margins, maneuver planning tuned to your propulsion system's delta-V constraints, or integration with an operational workflow commercial platforms don't expose. Keep the scale in mind. Planet and SpaceX are well-staffed teams, and both still rely on outside screening for the data. Budget for validation and flight-dynamics staff, and add a commercial tracking subscription where the free catalog isn't accurate enough for your orbit.

When buying makes sense

Buying makes sense when you don't have flight-dynamics staff or need better tracking than the free government catalog provides. LeoLabs sells observations from its own radar network and Slingshot Aerospace from its own telescope network, alongside analytics, and COMSPOC sells the catalog-building software that fuses sensor data. Better tracking data can tighten conjunction estimates for the objects that matter to your orbit. For small to mid-sized constellations without a dedicated team, a cloud-native conjunction service like Kayhan Pathfinder or OKAPI Orbits gives working screening and maneuver support without hiring for it. The screening algorithm itself isn't the scarce part, since the government publishes CDMs for free and NASA's probability code is public. What you're paying for is data quality, operations work you don't have to staff, and a methodology someone else maintains.

The desk read

Collision avoidance has two halves: the screening data and the analytics on top of it. The basic data is free. The U.S. Space Force provides conjunction data messages on Space-Track at no cost, and NASA publishes its collision-probability tools as open source. LeoLabs and Slingshot Aerospace sell more accurate tracking from their own sensor networks, COMSPOC sells the software that builds a catalog from such data, and that's the half where buying still has a clear edge. Kayhan Pathfinder and OKAPI Orbits work at the analytics layer and depend on the quality of what goes in.

The build case is documented. Planet built maneuver automation that checks planned SkySat maneuvers against Space-Track CDMs using its own thresholds, and SpaceX runs onboard autonomous collision avoidance on every Starlink satellite. Both are well-staffed teams, and both still rely on outside screening for the data. A team that wants custom probability thresholds or maneuver planning tuned to its propulsion can build that layer. The real questions are whether you have the flight-dynamics staff to validate and run it, and whether the free catalog is accurate enough for your orbit.

Representative vendors Kayhan Space (Pathfinder)COMSPOCOKAPI:Orbits (Aether)LeoLabs (Collision Avoidance) + 1 more, listed in the full index

Frequently asked

What is Space Situational Awareness & Conjunction Assessment (Collision Avoidance) Software?

Space Situational Awareness & Conjunction Assessment (Collision Avoidance) Software screens a satellite's predicted trajectory against a catalog of tracked objects, computes collision probabilities, and generates avoidance maneuver recommendations when risk thresholds are crossed. Operators use it to protect fleet assets, meet regulatory safety obligations, and maintain orbital slots in an increasingly congested environment.

When does building SSA & Conjunction Assessment software make sense?

Building makes sense at the analytics and automation layer when you need custom probability thresholds, maneuver planning tuned to your propulsion constraints, or workflow integration that commercial platforms don't support. Planet and SpaceX both run self-built collision-avoidance software in production on outside screening, the government's CDMs are free on Space-Track, and NASA publishes its probability code. Budget for validation and staff, and add commercial tracking data where the free catalog falls short.

When does buying SSA & Conjunction Assessment software make sense?

Buying makes sense for operators without flight-dynamics staff and for those that need more accurate tracking than the free government catalog. Cloud-native services like Kayhan Pathfinder and OKAPI Orbits deliver screening and maneuver support quickly, and LeoLabs adds tracking data from its own sensor network.

What are the main SSA & Conjunction Assessment software vendors?

Representative vendors include Kayhan Space (Pathfinder), COMSPOC, OKAPI:Orbits (Aether), LeoLabs (Collision Avoidance). B4 Pro includes the category score and the full vendor list.

How does the growing congestion in low Earth orbit affect this decision?

More satellites mean more close approaches to screen and act on, which makes the quality of your tracking data and the reliability of your process more consequential. It also makes automated maneuver planning, rather than analyst-in-the-loop review, more important for large constellations. SpaceX already runs onboard autonomous collision avoidance on every Starlink satellite.

The B4 Index scores every software category on two axes, strategic differentiation and AI feasibility, to classify it Build, Buy, Bridge, or Beware. See the full methodology.