Kajeka are pioneers in making complex data visually engaging, revealing hidden patterns and creating actionable insights. 

Every year the amount of data captured by the biological sciences and the business world grows exponentially. Problems arise when there is simply too much information to process and the ability to make fully informed decisions, become muddied or lost.

We create software for the analysis and visualisation of numerical matrices and networks. Our platforms produce intuitive visual representations of data structure, allowing your organisation to make more effective, more efficient, data-driven decisions..

We have over 10 years of experience developing network analysis technology

Our technology has been used in hundreds of publications and used by researchers the world over


Kajeka’s platforms have proven applications within Genomics, Transcriptomics, Single-Cell, Imaging, Pathways, Protein interaction and many more complex data sources.

Not limited to omics or just network data, our software can also identify patterns and relationships within complex numerical data

The output of many omics technologies are huge tables of measured variables with millions of samples or time points. Starting with a simple data table together with variable/sample attributes, Kajeka’s platforms can provide a rapid analysis pipeline to convert data into visually intuitive network representations.

Relationships between entities, e.g. genes, proteins, samples, can be explored and rapidly analysed, in a hypothesis-free manner. Our platforms can support the visualisation and analysis of any network, from any source, at scale.


Networks are a powerful visual medium for understanding relationships and associations between people or entities. They are a perfect way to tap into our innate ability to recognise patterns and structures within data, helping analysts make informed decisions, quickly.

Network analysis provides an alternative to conventional data-modelling approaches which are time consuming, question based analyses with limited scope for visualisation. Networks, also known as graphs, provide a versatile approach to modelling data from a large variety of industry sectors.

Transferring data into a network paradigm allows the use of algorithms, techniques, ideas and statistics previously developed in graph theory, engineering and computer science.  

“[Graphia] is an amazing software product. For someone like me who is devoted to systems biology analysis of tissues and diseases, it is a major step forwards.”

James P Bennett MD, PhD

President and CSO, Neurodegeneration Therapeutics Inc


Next Generation Graph Analytics

Designed and built from the ground up to provide a powerful and extendable network analysis environment suitable for many types of data from many sectors.

With support for millions of nodes, dynamic layout, advanced filtering, transformation, attribute handling, graph analytics and much more. Massive networks can be explored in real-time.

Graphia has been designed to integrate with external resources and be customised to meet the needs of a specific sector or enterprise customer.


Kajeka’s products and services have applications in a broad range of industries including:

Biosciences & Agritech

Omics analysis platforms have created a data deluge within these industries. Our software provides the means to explore and understand the relationships between genes, proteins, metabolites and cells.

 Law Enforcement & Defence

Interactions between individuals can take a many forms and are a challenge to track. Our software enables the analysis of large social networks, providing advanced means of tracking potential threats.

 Financial Services & Insurance

Understanding the relationships that drive financial markets is key to predicting future trends, Our software provides the means to explore such data quickly and in real time.



Kajeka’s software allows you to gain insight and tangible value from data. Whilst our products and services are at the cutting edge of visual analytics technology, they are also easy to use and gain instant and transformative results

Tools can be used by a non-specialist
Hypothesis-free data driven analyses
Perform predictive analyses
Integration of information from multiple sources
The handling of data from a small to vast scale
Trends and patterns can quickly be identified and acted upon



Our research in biological network analysis began nearly two decades ago, first at the Hinxton Genome Campus, near Cambridge and subsequently at University of Edinburgh. Confronted by an explosion in complex data describing the activity of genes, the aim was to transform the way we interpret biological data, which is often complex and difficult to understand with conventional approaches. The result was a series of revolutionary and ground-breaking visualisation techniques that have opened a new era of graph analyses.

Based within Edinburgh’s famous Roslin Institute, we are comprised of handpicked academics, researchers and entrepreneurs.

Les Gaw, CEO

Les leads the commercialisation of our business and has worked extensively with venture backed technology companies in either CEO or COO roles. His key skills involve driving business development and creating meaningful revenue streams within these companies. A graduate in Information Engineering at The University of Strathclyde, Les is passionate about ensuring product development is driven by customer need. He is also an enthusiastic member of the Institute of Directors.

Professor Tom Freeman, Chief Scientific Officer

Having gained his PhD from Imperial College, Tom began his long association with data driven
biology when he worked at the Wellcome Trust Genome Campus. He now leads the Systems
Immunology Group at the Roslin Institute, where his research combines the use of experimental
technologies to examine the immune system, together with the development of innovative
approaches to the analysis of complex data and systems. Tom was founder of Fios Genomics,
a company specialising in biological data analysis and in 2015, he founded Kajeka.

Paul Chowdhry, Chairman

Paul is a highly experienced board member whose proven skills in cusomer focus, leadership,
strategy and innovation have a strong part to play in the on-going development of our business.
He has led led large teams and has delivered product innovation, transformation programmes ,
planning processes and strategic direction to a wide variety of businesses. He has also played a
key role in several corporate investment, acquisition, intergration and sale transactions. Paul is
highly active within the Institute of Directors.

Professor David Hume, Non Executive Director

Professor Hume BScHons, PhD, FRSB, FMedSci, FRSE is a graduate of the Australian National University
and an internationally-known genome scientist.  His major research interests are in transcriptional
regulation, the function of cells of the immune system and genetic variation in disease susceptibility.
From 2007-2017, he was the Director of The Roslin Institute of the University of Edinburgh. Previously,
he headed the ARC Centre for Functional and Applied Genomics at the University of Queensland.  David
has had a long-term collaboration as a visiting scientist with the RIKEN Omics Research Centre in
Yokohama as part of the FANTOM Consortium.


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