Deliver imaging AI faster and more accurately with Zegami
Introducing the Machine Learning Suite. A unique set of cutting edge tools to help researchers and data scientists and subject matter experts to create, analyse and explain machine learning models, as well as, curate and annotate their training data.
How explainable is your AI?
Unlike traditional data management systems, Zegami’s visual data exploration platform gives you the power of ad hoc querying and visualization to allow you to understand your AI models and datasets – including both structured and unstructured data.
Zegami makes it simple to curate and annotate image data, identify outliers and assess the big picture while seeing the fine detail. Understand model performance and compare between model iterations, all within a single intuitive browser-based application.
Analyse & Explain
High throughput image analysis of large image data sets: extract insights, answer specific questions and qualify images for further study.
Perform exploratory data analysis over complex data with a visual and simple interface. Construct queries with no code or query language.
Quickly find outliers, edge cases and underperforming classes that can be missed using other techniques by ‘augmenting your ability to contextualise lots of information within a single view.
ML Model Evaluation
Understand and explain AI models to prove validity, demonstrate efficacy, and monitor production performance, especially in regulated environments.
Generate explainability heatmaps to better understand the inner workings of your models.
Investigate and analyse large image datasets to spot poorly labelled and mistagged images. Bring order to unstructured data.
Cell and tissue analysis
Visualize and query thousands of images and metadata from high content screening and genomics assays to look for trends and outliers in massive data sets. Use dimensionality reduction and cluster your images based on their properties to take cellular and tissue phenotyping to a new level.
Accelerate machine learning: use high throughput image annotation tools to curate high quality training data sets, rapidly annotate and tag images to rapidly iterate on machine learning models.
Evaluate the performance of your annotators or “crowd” to get a real-time overview of your labelling work.
Image Archive Enhancement
Enhance stale image archives: browse huge datasets at high level in exquisite detail, find rare or lost images and spot trends. Reinstate missing metadata.
Collaborate with your peers no matter where they reside, even over low bandwidth connections.
Make your data available to the world with data access controls. Allow users to export the original data and images for further offline analysis.
- Quickly find insights and publish findings to commercialise research faster.
- Real time visualisation and analysis.
- Collaborate from anywhere with our cloud based access.
- Higher project success rate, less waste on re-running experiments.
- Speed up quality control of large data sets by finding outliers or problems in the data.
- Iteratively test and adjust ML models to evaluate accuracy, identify biases and the specific data causing them.
- Exclude erroneous datapoints leading to higher quality ML models.
- Pass regulatory requirements more easily with explainable output from models.
- Rapidly build training data sets and spot missing, incomplete or inaccurate data leading to higher quality ML models.
- Uncover hidden data biases.
- Produce detailed segmentation masks to increase ML model accuracy.
- Significantly reduce the time and resources devoted to building custom tooling, image processing systems and data pipelines.
- Enhance existing data sets with dimensionality reduction / unsupervised machine learning views.
- Easily spot missing, incomplete or inaccurate metadata.
- Integrate custom ML models to extract features from images and make data sets more queryable.
Supported Data Types
.jpg, .png (8 and 16 bit colour depth), .gif, .tiff, DICOM, .svs, .vms, .vmu, .ndpi, .scn, .mrxs, .svslide, .bif
.xls, .xslx, .json, .csv, .tsv, .zip, SDK or API
Cloud – either yours or ours (Azure), hybrid or on-prem