AI enabled image analysis platform for scientific & medical imaging

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The Zegami platform helps you validate existing models by:

  • Reducing bias by avoiding overfitting across demographics or data sources
  • Identifying outliers and removing them from training data
  • Accurately benchmarking key data to minimise false positives and negatives
  • Demystifying data and machine learning algorithms for regulatory purposes
  • Improving the effectiveness and accuracy of existing models so you can make reliable predictions

Visualising Data on Screen

The Zegami Solution for your Industry

Machine Learning Data Curation

AI Lifecycle Management

Welcome to Zegami

Zegami has created a reliable, insightful AI-enabled platform for the analysis of scientific and medical imaging which places us at the forefront of this technology. The Zegami platform uses AI to facilitate the analysis, evaluation and curation of large data sets, with far-reaching implications for the scientific and medical communities. Zegami’s image visualisation platform allows you to easily find patterns, outliers and trends in large data sets, including images and visual data. Zegami helps to uncover bias and misclassifications in machine learning models to better understand how they work.

Curating data is a complicated and time-consuming process, particularly when working with large datasets containing unstructured data. AI and machine learning are key to the advancement of medical and scientific research and practise: when applied to the analysis of large and complex data sets, for example databases of medical images, machine learning can accurately identify patterns, trends and health outcomes which would otherwise be beyond the scope of human observation.

Zegami’s AI-enabled image analysis platform enables scientists and clinicians to extract meaningful insights from large datasets, based on patterns and outliers in the data. With Zegami, you can rapidly visualise related images and see precisely which ones an AI model is focusing on.

Our software offers an interactive solution to machine-learning: working with teams to create machine-learning models which help identify and understand potential problems or biases in training data, so that they can be eliminated to avoid misclassification, reduce error and improve outcomes.

Zegami provides scientists and clinicians with the accurate data visualisation tools needed to understand AI software and use it to its best advantage. Our platform demystifies machine learning, making way for constant improvement by consistently validating and testing new algorithms so that AI can be safely and reliably adopted in healthcare settings.

Why use Zegami?

Developing highly accurate, robust and unbiased AI is essential for future development in the worlds of science, business and medicine. Zegami’s leading-edge imaging software makes it possible to extract meaningful insights from big data and use those insights to inform and improve solutions. Featuring embedded intelligence, Zegami enables users to visually identify data quality issues with ease, and ensure that machine learning models are free from error and bias.

Zegami’s AI-enabled image analysis provides insights which:

  • Are clinically safe and validated in both clinical and research settings
  • Use machine learning to constantly update and improve upon training models
  • Manage AI bias, performance and surveillance over time
  • Maintain quality assurance through professional monitoring and validation
  • Satisfy regulatory compliance and certification requirements

Thanks to its leading-edge technology Zegami has numerous applications in the worlds of scientific research, engineering, healthcare and commercial data integration. Our current partnerships include:

University of Adelaide plant accelerator project
Zegami solves food supply issues in large automated greenhouses in Europe, Australia and the US, enabling researchers to view thousands of images simultaneously and identify patterns and anomalies in physiological and chemical traits.

Data scientists training machine learning models
Cancer Research UK is currently using Zegami’s imaging platform to develop a real-time cancer detection system which identifies cancerous lesions whilst a patient is being examined.

Data integration across silos
Commercial partners including Siemens and Honeywell have used the Zegami platform to extract meaningful insights from disparate data sources, cleaning data and simplifying the data management process to make it more efficient.

Latest demo collections

DICOM Mammograms

This mammogram dataset consists of 3486 DICOM (Digital Imaging and Communications in Medicine) images. It contains normal, benign, and malignant cases with verified pathology information.

Demo Introduction
Scan of a muscle

The Muscle Atlas

The Muscle Atlas created for the Institure of Myology, Sorbonne University, contains over a thousand of muscle biopsy images from people of different ages as well as animals.

Demo Introduction


COVID-19 lung X-ray insights. Cutting edge AI and visualisation technology can speed up efforts by researchers to develop new tools for diagnosis.

Demo Introduction

Cancer Diagnosis

Oesophageal cancer video frames to find cancer lesions to train the machine learning model.

Demo Introduction

Latest News & Events

On our radar

Here at Zegami, we always try to stay up to speed with the latest news, science and technology developments. Whether it’s innovations in machine learning, interesting applications of AI, or breakthroughs in healthcare digitalisation, our team’s on the lookout.

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Digital pathology: how medical imaging and AI are revolutionising the field

Technological developments in the field of digital pathology have made it easier to store, view and organise medical images. It’s also easier to engage and collaborate with other professionals, as well as quickly seek second opinions from other clinicians.

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Zegami’s Steve Taylor presents at the Medical Imaging Convention Virtual event

Hear from our Chief Scientific Officer, Steve Taylor, as he talks at the Medical Imaging Convention Virtual event about the use of artificial intelligence and medical imaging to understand disease.

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Our Clients

“Using Zegami has delivered significant cost savings to APPF . Because of the nature of the experiments, problems with the apparatus can render several days’ of results unusable. With Zegami, a variety of subtle problems can be quickly identified and timely interventions made to correct them.”

APPF Australian Phenomics Facility

George Sainsbury

Data Architect and Software Engineer

“Without zegami I wouldn’t be able to feasibly accomplish my project in a reasonable amount of time. It just allows me to go through large amount of information in batches rather than individually and it is a complete game changer.”


Lance Hentges


Our Partners

Let’s Talk

We’d love to understand the nature of your business or application, what data you have (both structured and unstructured), and help you visualise what’s possible with it.

Get a Demo