On-premise deployment for tight integration.
Bundled and ready to use. Download and run pixolution as a docker image in your infrastructure. Our docker support GPU and CPU and can supports almost any platform.
If you are running Apache Solr as search engine directly integrate pixolution as plug-in. Get the greatest Solr features while extending its feature set with Visual AI.
Decouple analysis and indexing as required.
Just provide the image URL when adding data. The image will be loaded and analyzed. The resulting data is then indexed in dedicated fields.
This is great if your image collection is not huge and reindexing uncommon.
If you pre-process your raw data and store it in a database, you can pre-process your images as well and store the analysis result as JSON. When indexing your data just use the pre-processed data.
This decouples the expensive analysis process from indexing and ensures you only have to analyze an image once.
pixolution is licensed on-premise. It runs on your own server network behind your firewall. You gain full control over your search system: Choose your own hardware for optimal performance, comply with data privacy requirements and backup policies and meet internal security requirements.
You’re prepared to grow. We support the Solr cloud mode with replication and sharding. Split and replicate your collection across several servers to handle massive parallel user requests and huge collection sizes. Searching in millions of images is easy.
We provide an HTTP REST-like API, making it interoperable and easy to integrate into your app or website. Several input and output formats are supported such as XML, JSON, CSV or binary. Many client API implementations are available for different languages including Java, PHP, Python, .NET and C#.
Our image search is lightning fast due to compressed image descriptors, smart filtering, and distributed search capabilities. Searching through millions of files takes less than a second.
Required fields and fieldtypes for visual data are configured automatically.