DeepMirror Spark – Early Access!

Two years ago, Andrea & I co-founded DeepMirror to accelerate AI adoption for biomedical data. In working with our clients, we quickly realised that the main hindrance for building and deploying AI is the scarcity of quality annotated data. Too often, our clients simply did not have enough annotated data available to train AI or it was too expensive or time-consuming to even consider. We listened and dove deep into the architectures that underly modern AI training to solve this problem.

After 1 year of hard work our team is proud to unveil DeepMirror spark – The agile AI growth platform that enables you to implement production-ready AI faster than ever before. Conventional AI requires the annotation of thousands of datapoints to train and maintain AI. With DeepMirror spark, you can reduce data annotation by up to 100x. Use it to hit the ground running in building and deploying biomedical AI in your organisation.

Early access to DeepMirror spark supports image data and allows you to:

  1. Upload image data (e.g. microscopy images)
  2. Annotate those images by hand
  3. Train an AI to learn your manual annotations from as little as 10 images
  4. Annotate more images with AI assistance to reduce edge cases and optimise AI performance
  5. Deploy your custom AI to use it on new unseen data and generate the insights you require (API access available!).

If you are keen to deploy powerful small-data AI in your organisation look no further. Give DeepMirror spark  a try now for your image data or get in touch if you want to use it on other data (e.g. genomic & feature based data). Please let us know if you need any help with DeepMirror spark – we can arrange remote sessions for help and/or discussing any details!

You can find DeepMirror spark here:

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