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Deep learning for sparse or noisy data with proven solutions in advanced materials and drug discovery

Reducing cost and risk by accurately modelling expensive experimental datapoints from minimal data

Integrated software to optimise processes and reduce costs, used online or integrated within existing workflows

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Use Cases

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Our unique approach

We have developed a unique capability to train and predict models from incomplete data. The technology can be used to link large, easy to acquire, databases with small, hard to acquire datasets. Generated models can be used to design, predict and identify errors.

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Suite of Tools

Our algorithms have been wrapped up into our core Alchemite™ engine, enabling a number of software solutions, allowing easy integration in internal workflows or making use of on-demand cloud compute via fully hosted version.

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Drug Discovery

Given a fragmented dataset the algorithm can learn the underlying correlations to estimate the missing knowledge of how candidate drugs act on proteins and therefore help clients to design new drug cocktails to activate the right proteins to cure disease

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Material Design

The million commercially available materials are characterized by hundreds of properties Our technology learns the underlying correlations to estimate the missing properties and propose a material with the target properties


Intellegens is developing a series of application specific AI modules, designed to address specific, high value, data analysis bottlenecks that we are uncovering through our discussions with existing and new customers.


The first commercially availble product Alchemite™, has been specifically built to work with sparse data and is capable of learning from datasets as little as 0.05% complete.
The algorithm has proven commercial applications in materials design and drug discovery. Trained models can be used for predictions, error detection and parameter optimisation (design).

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Intellegens is a spin-out from the University of Cambridge that has developed a unique Artificial Intelligence (AI) method for training neural networks from incomplete data sets. The technique, developed in the Department of Physics, has been applied in drug discovery and material design but as the technique is generic it can be applied to many domains where there is big, incomplete data.

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Dr Gareth Conduit

Gareth Conduit has a track record of applying artificial intelligence to solve real-world problems, with research contracts held with companies spanning from materials science to healthcare. Gareth holds an academic position at the University of Cambridge and is a Fellow of Gonville & Caius College.

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Ben Pellegrini

Ben is an expert in big data and cloud based platforms who has delivered full-stack, commercial solutions to numerous clients in scientific, retail and health sectors. Ben has worked with several startups, large corporates and public sector clients.

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Dr Tom Whitehead

Tom recently completed his PhD at the University of Cambridge. Tom is leading the application of our novel deep learning approaches to a wide variety of industrial applications, alongside the development of our internal suite of tools and algorithms.

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Dr Robert Parini

PhD in Mathematics from the University of York. Robert is leading the development of our platform to integrate and optimise our new algorithms in a scalable, secure and robust manner.

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Graham Snudden

Graham was co-founder and VP Engineering at BlueGnome, a specialist in the screening of genetic abnormalities associated with developmental delay, cancer and infertility, which was acquired by US giant Illumina in 2012.

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Dr Elaine Loukes

Elaine has worked as an early-stage tech investment manager since 2001. She has extensive experience in all stages of the investment process including due diligence, financial modelling, deal negotiation and investment management.


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Alchemite designs new alloy for 3D printing project

April 2019
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Biorelate and Intellegens secure InnovateUK funding

February 2019
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Assay imputation with deep learning

February 2019
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Design of alloy for direct laser deposition

February 2019
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Modern methods in drug discovery IPT

December 2018
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Presentation on Streamlining Drug Discovery

October 2018
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Novel deep learning drug discovery platform gets £1 million innovation boost

September 2018
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AI in advanced materials at Engineering Materials Live

September 2018
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Optibrium and Intellegens Collaboration

September 2018
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10 Most Innovative Deep Learning Solution Providers 2018

September 2018
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Materials validation and imputation with neural network

February 2018
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Full stack Python developer

We are looking to appoint a python based developer to help build out our Alchemite™ platform and deliver on existing and future projects and products.

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Front end developer

We are looking for a front end developer who can build clean and robust user interfaces, with a passion for UI and UX that can maximise the impact and accessibility of the insights delivered by our core deep learning technology.

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Please get in touch to see how we can help

See how our unique AI can solve real world problems