Zegami Software

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About Zegami

Zegami is a data visualization solution that combines cutting edge tools like machine learning to help businesses and research organizations gain insights by exploring large datasets. With Zegami, you can visualize and analyze unstructured data such as images and video. It enables you to examine large image datasets simultaneously on a screen and spot patterns or anomalies. Data scientists using the solution can train their machine learning models. Cancer Research UK aims to develop a cancer detection system using Zegami, highlighting cancerous lesions on the video as the patient is being examined in real-time. Companies such as Siemens and Honeywell are using Zegami to extract insights and clarify issues/questions acquired from disparate data sources, facili...

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Zegami User Reviews


Showing 2 reviews


University of Oxford

Verified reviewer

Company size: 11-50 employees

Industry: Research

Time used: Less than 12 months

Review Source: Capterra



Customer support




Reviewed December 2019

Zegami's functionality review

The overall experience with Zegami has been great! I really like using the software and it helps spots trends in my data much quicker than in any other way. I think is very visually pleasing and easy to use.


What I like most about the Zegami software are the different views one can have of the data, especially the graph and scatter view and the fact that one can change the axes. I also like the filtering functionality and also the fact that is so easy and smooth to create a collection and also edit it.


Sometimes the zoom functionality is not working as I would like e.g. sometimes it zooms too much into a tile and some other times it zoome and shows 4 half tiles.


The Plant Accelerator

Verified reviewer

Time used: Free Trial

Review Source: Capterra



Customer support


Reviewed March 2015

We are really excited about Zegami!

The first image collection we loaded into Zegami is an experiment looking at nitrogen use in wheat growth. With our existing tools, we were able to see a significant drop in the Projected Shoot Area measurement on day 60 of the experiment. (Projected Shoot Area is the area in pixels of the plant viewable in that 2D image.) Looking at the images one-by-one, our initial reaction was that the drop was due to the plant entering the next phase of development - when energy goes from growing leaves into producing flowers. It wasn't until we used Zegami to look at the surrounding images that we realised that they actually looked much brighter. A bit more investigation turned up the fact that our imaging system had stopped for 3 hours in the early morning before being corrected. This meant that almost half of the nearly 500 plants were imaged in the middle of the day instead of the early morning for that day. While this outage had been noted somewhere, it wasn't expected that the changes in ambient light would have had such a drastic effect on the analytical results and Zegami made it incredibly easy to track down this blip in the results.

Response from Zegami

Thank you for the feedback!

Replied November 2019