CelestCore helps satellite operators turn collision risk data into defensible maneuver decisions, including knowing when the data itself should not be trusted.
Satellite operators receive hundreds of collision alerts every week. Each one must be evaluated because the consequences of getting it wrong are permanent. An unnecessary maneuver wastes fuel and shortens mission life. A missed threat can destroy an asset.
Existing systems deliver tracking data and risk metrics, but they stop at the operator's screen. Tracking, risk analysis and maneuver planning address different parts of the conjunction problem. CelestCore connects them at the decision layer, where evidence quality, timing, fleet constraints and independent verification determine whether the operator should act, monitor or defer.
The bottleneck is no longer collecting orbital data.
The bottleneck is making the decision.
Operators often monitor alerts while tracking improves because many resolve naturally. The decisions that matter are the ones where waiting no longer helps. CelestCore determines when continued monitoring remains useful, when the maneuver window requires action and when the available evidence is too weak to support a recommendation. The May 2024 Gannon solar storm showed what happens when the data stops reflecting reality. Changes in the upper atmosphere altered satellite paths faster than forecasts could keep up, while thousands of satellites maneuvered unexpectedly. Reliable collision warnings became nearly impossible for three days.
NASA missions supported by CARA are backed by dedicated analysts who review close approaches, compare multiple methods and advise on decisions. CelestCore brings that analytical rigor into software for commercial operators that do not have a dedicated analyst team behind every conjunction.
The system ingests conjunction data from existing providers, assesses data quality, optimizes maneuver options across fleet constraints and delivers confidence-scored recommendations with full traceability.
Analyzes how uncertainty signals evolve across successive data updates. Detects when risk data is physically inconsistent. Tracking gaps, estimation resets, atmospheric model failures. All flagged before any decision is made.
Evaluates maneuver options across an entire constellation simultaneously. Fuel budgets, mission schedules, overlapping alerts. All weighted by how much the system trusts each conjunction's data.
Every recommendation passes through a separate safety verification path that cannot be bypassed or influenced by the advisory system. When confidence is insufficient, the system formally declines to recommend rather than producing an answer the data cannot support.
A view into the decision workflow an analyst could use day to day. The fleet view below shows a hypothetical workday for an operator running 80 satellites.
CelestCore does not execute maneuvers. Every recommendation is advisory and every override is logged. The operator is always the one in command.
The analyst works through three events while the system resolves the other thirty-seven through the configured workflow. The same pattern holds from 80 satellites to several thousand.
Validated against NASA CARA's published benchmark. Real conjunction events involving Hubble, TERRA, AQUA, ICESat-2 and other high-value assets.
Across three updates, the standard 2D calculation returned collision probabilities from 3.86 × 10-168 to 4.51 × 10-81. CelestCore recorded physically unrealistic covariance behavior, insufficient evidence of consistent covariance growth, low segment confidence and an unstable covariance structure. It assigned the combined event a DEFER posture rather than issuing an unsupported recommendation.
CARA's higher-fidelity SDMC reference placed the probability between 1.30 × 10-6 and 1.17 × 10-5. The entire range exceeded NASA's 1 × 10-7 level for operational attention. It remained below the default 7 × 10-5 threshold for evaluating maneuver options and the 1 × 10-4 mitigation threshold.
Sources: CelestCore reproducible audit artifact; NASA CARA Close Approach Risk Assessment; NASA Differential-Drag Decision Aid.
In 37 of NASA CARA's 53 reference cases, finite covariance-scale profiling found a higher interior candidate collision-probability estimate than the endpoint value. This candidate is not a certified continuous bound. The operational-data evaluation covered 162,634 CDM-derived rows grouped into 13,154 ESA conjunction-event histories.
My background spans machine learning systems, orbital data analysis and decision system architecture.
CelestCore was born from a pattern that I often noticed. Many maneuver decisions were being made on data that looked clean but was not. The tools operators had were not built to tell them the difference. What they wanted was not more alerts or prettier dashboards. They wanted to know when to trust the number in front of them; that question was not being answered anywhere in the stack. As such, I built CelestCore as an answer and at a cost and commitment level that fits operators of diverse workflows, missions and fleet sizes.