Build with us

We build AI systems that are highly interpretable, embedding creative and scientific knowledge via a range of modelling and agentic techniques, including physics-informed machine learning architectures. Our design is intended to amplify human capability, not automate it. Whether your challenge involves mapping a combinatorial explosion of variables—like our groundbreaking work scaling woodwind acoustics to millions of configurations—or making sense of complex sensory, biomedical or financial datasets, we translate human intent into expressive AI capabilities.

Our work has won engineering awards and design awards, and has been published in international journals. If your organisation is ready to create an expressive AI capability, contact us to discuss how we could build it together.

Engineering posts from the blog...

Dear Executives: Engineering is art, not labour

Great ideas are like great art: they can be used and studied over and over, reaping large and concentrated profits for their owners. It is essential to develop and broaden the capabilities of engineers for greater output and more competitive ideas.
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It’s not too late for engineers to be great statisticians

Engineers should have the breadth of skill, from mathematics to computing to domain expertise to communication, to make outstanding statisticians.
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Big data pitfalls for engineers from the Financial Times

Software developers can easily run their programs on thousands or even millions of test files from their archives, but the opportunities provided by large datasets can be elusive.
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Why have one mentor when you can have a network?

Your world is not your mentor’s world. In my experience, it’s more useful to have a network of mentors, each offering you a different viewpoint when you need advice.
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