Kailume replaces opaque predictions with readable equations - the only AI output regulators, patent attorneys, and peer reviewers will accept.
Designed and powered by world-leading AI experts at The Kids Research Institute Australia, one of the largest and most successful medical institutes in the country.
Not a prediction. An equation.
Readable. Patentable. Defensible.
// what's.hiding
Kailume is a scientific discovery service. Using proprietary genetic programming technology, it extracts transparent, interpretable mathematical relationships from your data - real equations, not black boxes.
Most AI gives you one model and calls it best. But best for whom? The engineer who needs simplicity? The regulator who needs transparency? The researcher who wants mechanistic insight? Kailume produces a portfolio of valid equations, each representing a different balance between accuracy, simplicity, and practicality. Every output is readable, testable, publishable, and ready for regulatory submission. Your team chooses the one that fits.
Initially built for healthcare and life sciences, Kailume's approach applies wherever structured data meets a need for models that people can actually understand and trust - and wherever your findings need to survive staff turnover, vendor changes, and regulatory scrutiny.
// why.choose
Standard AI optimises for accuracy. Kailume optimises for accuracy, transparency, and your ability to defend every result to anyone who matters - the difference between a result you can publish and one you can only hope holds up.
01
Standard explainability tools build a black-box model first, then approximate an explanation afterwards. Kailume outputs are the explanation - every result is a human-readable formula that domain experts, reviewers, and regulators can assess directly. No post-hoc interpretation layer needed.
02
Kailume returns a curated set of high-performing alternatives, each using different variable combinations and balancing objectives differently. You choose the formula that fits your real-world constraints - clinical, operational, or IP-related.
03
Kailume excels at regression and classification on tabular data: clinical datasets, experimental results, process parameters, biomarker panels. It handles automatic feature selection and high-dimensional problems, and delivers results ready for deployment.
04
Most tools optimise for accuracy alone. Kailume optimises across four or more objectives simultaneously - including practical measurability and feature independence - so results are accurate and use variables you can actually measure and act on.
// the.origins
Kailume was invented by Timo Lassmann, Associate Professor at the University of Western Australia and lead researcher at The Kids Research Institute Australia. Timo earned his PhD in Functional Genomics at the Karolinska Institute and spent a decade at RIKEN in Japan leading data analysis for the landmark FANTOM4 and FANTOM5 projects - the most comprehensive atlases of gene regulation ever produced.
He subsequently served as lead analyst for the ENCODE project, the international effort to map every functional element in the human genome. Since 2014, his group at The Kids Research Institute Australia has pioneered AI tools for rare disease diagnosis - work published in Nature in 2026.
The challenge Timo has faced throughout his career - extracting reliable, explainable relationships from vast and noisy biological datasets - is the same challenge facing every organisation now required to justify its AI to regulators. Kailume is his answer.
The expertise behind Kailume is the same expertise that built modern genomics. 55,000+ citations. 287 peer-reviewed papers. Powered by The Kids Research Institute Australia.
// get.in.touch
If you're working with data in a field where your findings need to be explained, defended, or published, we'd like to hear from you.
Data privacy
Your data is never retained between engagements or used to train shared models.
Turnaround
Most engagements deliver a full equation portfolio within days of receiving the dataset.