Models
Entity Extraction for Unity
Extract entities from any source (E.g., text, pdf, url).
Product Content generation
This is a newer version of our content generation model. It uses and intermediate step of extracting product specific features and specifications from the description. The model then generates or recreates a product's description using information from its title, brand, and either a set of product features or an old description. Optionally, choose what audience the description should be marketed to (e.g. "parents" or "professional musicians", and a tone for the new description (e.g. "fun" or "technical"). To specifically avoid terms, add them to the Avoid field (e.g. "Warning", "warranty") or to specifically include them, add them to the Keywords field.
Relist Product
Takes a product description, title, and additional optional parameters, and generates a new title ( < 80 characters) a new short description of the product ( < 160 characters) a new long description of the product ( < 500 characters)
Image Super Resolution
This model helps to increase the resolution of an image using ML techniques. Existing algorithm based techniques (such as bicubic) may leave artifacts or make it blurry. ML based approaches produce better resolution.
Defect Detection
Visual defect detection uses computer vision to identify flaws and defects in manufactured items. This model has been trained on metal sheets and plates and can identify flaws, cracks, dents and scratches on sheets and plates.