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Do it yourself AI for image analysis

Aiforia Create is intuitive to use, no coding or AI experience is needed, only the expertise you hold in your own field.

Aiforia Create is optimized to minimize the annotations needed for it to learn

It lives in our cloud platform so all you need is internet access to upload and store your images to get started.

How does Aiforia Create work?

Benefits of Aiforia Create



Measurements of spatial and morphological metrics for identified objects

Multi-class object detection

  • Tedious quantification tasks or identification of rare objects or features

  • Possible from whole slide images

Combine with automated region of interest selection to automate the whole image analysis task



Application examples
  • Nerve cell counting in Parkinson’s disease
  • Fat and fibrosis measurements in liver tissue (NASH, NAFLD)
  • Measurements between stromal CD8+ cells and lung cancer tumor borders
  • Malaria parasite detection from blood smear


Multi-class semantic segmentation

  • Automated segmentation of image patterns

  • Quantifying surface areas and a versatile range of spatial metrics

Combine with object quantification to automate the whole image analysis task



Application examples
  • Tumor grading and tumor burden
  • To detect TH+ neuronal areas and plaques
  • Tissue architecture, for example: portal areas, hepatocytes, parenchyme, capsule, biliary ducts, veins
  • Identification and quantification of tissue or cell lesions caused by infectious diseases


Regression models predicting continuous values

  • Measuring depth of color, intensity of staining, patient outcomes



Application examples
  • Cell and nucleus size
  • Patient survival time
  • Astrocyte reactivity
  • Drug-dose response

Explore the research areas Aiforia is already supporting

Aiforia’s analysis capacity is scalable and powerful. Deep learning AI relies on high-performing graphics processing units (GPUs). Aiforia’s platform is powered by NVIDIA’s GPUs, some of the world’s most powerful units built specifically for deep learning.

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