DeepMirror Spark- grow AI from scratch with less annotations
Most datasets start small and stay small. But AI currently only works for big data. We use semi-supervised learning to make AI useable from day 1. In contrast to conventional AI training, our platform can extract information from small datasets by using our proprietary training algorithm. Use it to hit the ground running as you deploy biomedical AI in your organisation.
Our early access app now allows you to submit and annotate image data (e.g. microscopy or radiology data) to train cutting edge AI architectures. Only a few images are needed – then, after validating AI predictions and correcting edge cases, you can deploy your custom biomedical AI.
Scroll to our case studies below to see for yourself how our clients used DeepMirror Spark to create AI solutions that were able to learn from small datasets to speed up workflows and gather new insights.
DeepMirror Spark VS conventional AI
How to create an AI with DeepMirror Spark
Grow custom AI from scratch within hours before curating vast amounts of data
Keep up with changing world by adding more data and adjust your models
AI solutions come with powerful & customisable analytics for biomedical data so that you can extract the insights you need
What clients say about us
Our Team
Dr Maximilian Jakobs
Co-Founder, CEO
Dr Andrea Dimitracopoulos
Co-Founder, President
Ryan Greenhalgh
Founding Engineer
Ashna Ahmad
Business Development
Amir Shirian
Machine Learning
