Sachcontrol Gmbh

Lars Rietzschel

Andrey Lutich

In one embodiment, a method includes accessing an image of a damaged object. The method further includes determining, using a plurality of image segmentation models, a plurality of objects in the image. The method further includes determining, using a plurality of visual inference models and the determined plurality of objects from the image segmentation models, a repair-relevant property vector for the damaged object in the image. The repair-relevant property vector includes a plurality of damaged object properties. The method further includes generating a repair report using the repair-relevant property vector and a price catalogue. The repair report includes an indication of the damaged object and a price associated with the repair or replacement of the damaged object. The method further includes providing the generated report for display on an electronic display device.

Repair estimation based on images

In one embodiment, a method includes receiving an invoice. The invoice includes invoice positions and each of the invoice positions includes a position text. The method also includes converting each word and number of the position text of each invoice position to a word embedding vector, summing the word embedding vectors for each invoice position to generate a word vector for each invoice position, and concatenating the word vector and a number vector of each invoice position to generate a position vector for each invoice position. The method further includes generating a first combined position vector for a first invoice position, generating a second combined position vector for a second invoice position, generating an invoice vector by summing the first and second combined position vectors, comparing the invoice vector to a fraud detection parameter, and determining whether the invoice is indicative of fraud based on the comparison.

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Bannewitz, Germany

Lars Rietzschel