Yes, it's private. Our intelligent photo search is built on the knowledge behind ChatGPT's success - but our technology is owned by us and built from the ground up by us. This means that your data is NOT used for training and is NOT passed on to third parties.

Our system uses pre-trained AI models for image analysis and natural language processing. These models have been trained on large, external datasets and Onlime does no additional training using internal customer data.

Here's how Onlime Intelligent Image Search works:

1. We use pre-trained AI models: We use AI models that are already trained on large external datasets of images and texts. We do NOT pre-train the models from your images, ensuring a completely secure and private service.

2. We convert images to vectors: When you upload images to Onlime, our AI model automatically analyses the content of each image and creates a vector representation of each image. A vector is a matrix of hundreds of numbers that cannot be read by humans, but allows you to compare one vector to another.

3. We convert the search query into a vector: When you describe the image you're looking for, we also convert the search term into a vector representation.

4. We compare the vectors: Now we calculate the distance between the search vector created from your search and the image vectors associated with each image you have stored with us. If the distance between the vectors is small, it means that the vectors are similar. Then we say that the similarity score between the two vectors (the search and the image) is high.

5. We show you the result: We sort the images from highest to lowest similarity score so you can see the most accurate and relevant images based on your search request.

Current limitations of our intelligent image search:

• The search function does not currently have personalised face recognition, i.e. the ability to tag specific people by name. However, the model understands and recognises faces and by using the "Find similar" tool you can find images that have the same people in them. Enabling tagging of people is something we will most likely add in the near future!

• The location of the image, which can be found in the metadata, is not yet integrated into the search, which means the geographical search is limited. However, the model recognises famous places, cities and regions, so searching for "Eiffel Tower in France" or "Taj Mahal" will give very accurate results. It can also understand whether images were taken in New York or London, as the model has been trained on millions of images.

• The search currently does not support searching by time periods

• Search is limited by the visual content of your images, which may not always represent exactly what you are searching for (if the quality of the image is poor, the angle is strange, etc.).

"Happy children in front of a mountain"

"Niños felices frente a una montaña"

「山の前で幸せな子供たち」