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What We Do

Algorithmic approaches can discover optima in truly astronomical search spaces by using non-deterministic approaches such as population-based algorithms, training networks of inference, predictive analytics and even optimization with quantum computation and quantum-inspired processing. We design, develop and deliver such solutions as well as speeding deterministic algorithms that are amenable to high performance processing such as parallel processing, data-parallel processing and specialist processors.

Discovery and optimization can speed research and development by accelerating the Model-Hypothesise-Experiment cycle. We aim to help scientists, engineers, researchers and product developers by, for example, inducing and tuning their models, improving simulations, discovering and expanding hypotheses by tuning parameters and optimizing experiments through DoE, evolving experiment definitions and optimizing high throughput automations.

  • Developing new algorithms
  • Speeding and Optimizing existing algorithms
  • Finding faster platforms
  • Integrating your algorithm with other systems and workflows