[ Product · Photon ]

A full conjunction-assessment pipeline, delivered as software.

No new hardware, just software taking in available data and putting out a clear and understandable plan for the team to review.

01 · Ingest

One catalog, sharpened by your own ephemerides

Photon downloads the public CelesTrak catalog (GP/OMM) about every 2 hours — CelesTrak publishes no faster — and keeps the history of the element sets it has downloaded. When you attach your own CCSDS OEM ephemeris to a fleet satellite, Photon positions that satellite from your ephemeris instead of its public elements for as long as the ephemeris covers.

GP / OMM EPHEMERIS UPLOAD
GP / OMM EPHEMERIS MERGE your OEM wins ONE CATALOG
02 · Analyze

Prioritized by estimated probability, not just distance

Public element sets come without a covariance, so Photon models one: it estimates how far off an element set is likely to be from its age, using how much successive published sets of the same object disagree, refitted daily per orbit class and object type from the catalog archive. That modelled covariance feeds a two-dimensional short-encounter collision probability for each close approach — an estimated Pc, labelled with its basis, used to rank what deserves attention. It is not the probability a tracking network computes. Optional ML re-ranks alerts by what your team actually acts on and flags satellites whose orbits look out of family.

LOOK-AHEAD SCREENING MODELLED COVARIANCE RANKED BY ESTIMATED Pc
COVARIANCE DEFAULT FITTED RANKED BY EST. Pc
03 · Alert

The right warning, where the team already lives

Deduplicated, severity-ranked alerts arrive by Slack, email, webhook or API — with the full encounter context attached, prioritized using configurable risk thresholds.

SLACK EMAIL WEBHOOK REST API
RAW DEDUP · SEVERITY est. Pc > threshold SLACK EMAIL WEBHOOK API dedup + threshold filter
04 · Maneuver

Low-Δv avoidance, simulated before you decide

Photon generates candidate avoidance burns — impulsive, on public orbit data, under stated modelling assumptions — looks for low-Δv ones, simulates their effects, and hands them over for operator review. They are candidates, not guaranteed-minimum or globally optimal solutions, and Photon never commands a spacecraft: your flight dynamics team verifies and decides.

CLOHESSY–WILTSHIRE Δv + COMPONENTS DECISION-SUPPORT · YOU COMMAND
THREAT Δv miss ↑ new track original
[ Screening, plainly ]

How often it runs, and how sure it is

Photon is a screening tool, not a live feed. Server-side screening is a scheduled batch over public data, and what it reports is an estimate built on a modelled uncertainty. Here are the numbers, and the limits that come with them.

2 h
SCREENING CYCLE

The server re-screens every licensed organization's saved fleets on this schedule, and an alert can only be as fresh as the last cycle. It is not continuous.

7 days
LOOK-AHEAD PER RUN

Public element sets lose accuracy with age, so a Pc for an approach days away is usually diluted and says little; the nearer the approach, the more it means.

< 5 km
APPROACHES KEPT

Each run keeps a satellite's closest approaches under this distance — at most 25 per satellite — and an organization's rule decides which of them alert.

~2 h
CATALOG REFRESH

The public catalog is re-downloaded about this often, and an object's own element set may be older still. A screen uses what was last published, not where the object is this second.

An estimate is not an operator's data

Public element sets carry no uncertainty of their own, so Photon's covariance, and the Pc computed from it, are modelled. The numbers your own tracking and your conjunction messages carry are a different kind of thing.

What Photon does not claim
[ Data handling ]

Where your data goes

Photon is a desktop app with a cloud account, so some work happens on your computer and some on our server. This is which, and what leaves your machine. The privacy page covers the rest, including how long things are kept.

Runs on your computer
What our server receives
What needs the internet
CDMs and OEMs
[ How it's built ]

Built for real orbits, honest about the rest

A Rust core does the number-crunching; Python runs the AI and the 3D console. Everything is screening-level — Photon proposes, an operator decides.

~20K
PUBLIC CATALOG OBJECTS

Your fleet is screened against the public CelesTrak catalog — payloads, rocket bodies and tracked debris. Objects missing from it are not screened.

Local
PHYSICS ON YOUR MACHINE

Propagation and screening run on the operator's machine. Once you are signed in they don't need a live connection.

0
PURE SOFTWARE

Runs on public tracking data and feeds already in place. Nothing to install in orbit.

Logged
AI USE, ON YOUR MACHINE

Every AI generation is logged locally — metadata by default, full prompts only if you switch that on — so you can see when and how AI was used. Its wording is conservative and screening-level.

See Photon on your own fleet

Bring your catalog IDs and we'll walk through a screen of your own fleet with you.

Ask for a walk-through