Leverage our decades of experience in science and industry
Our team, headed by A/Prof. Ben Fulcher, has decades of experience providing tailored time-series analysis solutions for analysts and researchers.
Our team has developed a widely adopted family of open-source software for solving complex time-series analysis problems, including hctsa (the largest-ever collection of over 7000 time-series features) and catch22 (averages over 40k Python downloads per month).
Our time-series analysis tools have been used across fields including biomedicine, neuroscience, astronomy, meteorology, energy, and finance — from classifying stars in NASA's Kepler Mission, to discovering signatures of fatal neonatal illness, to earthquake detection.
We introduced and implemented the highly comparative time-series analysis approach which facilitates comparison across thousands of powerful time-series analysis methods to tailor and adapt those most suitable to a given problem.
This allows analysts to draw on the most powerful time-series theory and algorithms, which can also provide understanding.
Concentrating the algorithmic complexity in the analysis methods often allows us to overcome limitations of deep neural network-based analytics, providing reliably high accuracy through more scalable and interpretable approaches.
We have worked with startups and established companies in a wide range of industries.
Obtain commercial licenses for our existing software, backed by extensive published validation for rapid deployment.
Drawing on thousands of candidate methods, we deliver compact, interpretable, and computationally efficient algorithms for a given time-series problem.
A/Prof. Fulcher offers hands-on consulting for teams integrating time-series analysis into their products or research workflows — from feature design and validation through to pipeline architecture and interpretation.