Perseus. The future comes with a formula.

Ready to unlock the future? Perseus clusters the present to calculate the future. For leaders who don’t have time to be wrong. Predict the weather, why not predict the future? It’s not rocket science, quite, just maths. We are busy road testing. Please let us know below if you would like updates?

See patterns, not chaos.

We are early in the development journey but we have a hunch that Perseus will be pretty fantastic at turning time series, longitudinal data into something meaningful for large organisations. If you have a suggestion on the direction of Perseus, we’re all ears..

  • Spot patterns hiding inside your data

    Dr Andrew Smith

  • Perseus is for people who like control

    Dr Andrew Smith

  • and want tools that respect their time — and their data.

    Dr Andrew Smith

Because guessing is for weather apps.

Think of it like this: your data is a giant messy cloud. Perseus spots the patterns hiding inside, groups them together, and shows where things are heading—before they actually get there.

Perseus clusters the present to calculate the future.

Track progress over time

In systems made up of many individual people—like students going through an education program—we can track their progress over time using different types of information, like test scores or course completion. These individual journeys can look very different and are often influenced by many unpredictable factors.

This software introduces a new way to summarize and compare those journeys. Instead of looking at each data point individually, we use a mathematical tool (a type of transformation) to turn a person’s full history into a simpler form that still contains most of the information. This lets us group similar journeys together and even predict how someone's journey might end based on others like them.

We also show how to reverse the process—so we can look at a group and see what a “typical” journey in that group looks like. Best of all, this can be done as the data comes in, which means we can use it in real time. We show how this method works using real data from students training to become teachers.

Outsource the guess work to Perseus

Can you collapse time?

Tracking progress doesn’t have to be a headache.

When you’re looking at big systems made up of lots of individual people — like students working through a training program — everyone’s path looks different. Some fly through, some hit bumps, some take surprising detours. Traditional tracking just piles up test scores, completion rates, and endless spreadsheets, but it doesn’t really tell the story.

Perseus takes a different approach. Instead of staring at every data point separately, we turn someone’s entire journey into a single, smarter snapshot — using math that keeps all the important stuff intact. This lets us:

  • Group similar journeys together so you see patterns instead of chaos.

  • Predict where someone’s headed by comparing them to others who’ve walked a similar path.

  • Reverse the view to see what a “typical” journey looks like inside any group.

And the best part? It works as the data comes in. No waiting for end-of-year reports. No guessing games. Just real insight, in real time.

We’ve already tested this on real student data — future teachers — to show how it works. The result? A clearer, faster way to understand progress, spot problems early, and actually help people succeed.

Imagine using it for workforce planning? Knowing who is going to leave, knowing who the future leaders are so you can invest in their success, or halting a star from leaving..

Why Perseus?

Early warnings

So you know which students (or employees, or patients, or users) might need help before they fail or drop out.

Actionable patterns.

Instead of waiting until the program ends, you can see what’s happening as it happens and step in while it still matters.

Perseus. Just know

A way to make decisions without guessing — no crystal ball, no hand-waving, just math. This isn’t about squeezing people into boxes or pretending humans are predictable machines. It’s about respecting the complexity of real life while still finding useful, honest signals hidden in the noise.

The takeaway? When you treat individual progress as a path rather than a pile of numbers, it’s much easier to help people succeed. And you can do it live, without waiting for the end of the program to find out what went wrong.