VectorTree Gets EU Funding to Build Advanced AI Database

The project is part of the EU Funds Investment Programme 2021–2027, with a total budget of €943,052.28, of which €565,831.38 comes from the European Union.

VectorTree is developing a cloud-based Advanced Vector Database (AVD) to support AI systems. The database uses Videntifier’s NV-tree algorithm known for handling large volumes of visual data quickly and efficiently.

Ari Kristinn Jónsson, CEO of VectorTree, says, “As AI systems increasingly process vast volumes of unstructured data—such as images, video, text, audio, and sensor input—they require scalable infrastructure. With the EU’s support, we’re building a vector database that not only scales, but also changes how data for AI is retrieved, increasing accuracy without relying solely on exact matches.”

AI systems often deal with unstructured data like text, images, or videos. To make sense of it they convert this data into vector embeddings—numbers that capture the important features. VectorTree’s AVD is designed to store these embeddings and perform quick similarity searches, allowing AI to compare new inputs with stored data and instantly find relevant matches.

Read Also - Venture.Community Launches Co-Fund to Support Early-Stage Founders

A standout feature of AVD is vector clustering. Unlike regular databases that give only one match AVD can find and group multiple related results. For example, on video platforms, it can identify and group scenes with similar visuals and timing to recommend content users might enjoy. In legal tech, it can match older cases that use different wording but have similar meanings, improving research. In healthcare, it can bring up previous patient cases with similar symptoms, helping doctors make informed decisions.

Another strength of AVD is its ability to scale. While most vector databases can handle a few billion vectors, AVD is being built to manage tens or even hundreds of billions—without slowing down or losing accuracy. This is possible thanks to Videntifier’s NV-tree technology, which is already trusted by organizations like INTERPOL and Meta for large-scale visual searches.

With support from the European Union, VectorTree aims to release AVD for early sales in 2025 and continue developing it through early 2027. The goal is to provide AI researchers, developers, and businesses with a high-performance platform built for massive data and fast results.

Videntifier Technologies Ehf is an Iceland-based company founded in 2008. It builds video identification tools to help organisations detect illegal content online.

The company works with law enforcement, online platforms, and child protection hotlines to manage large amounts of video and image data. A key partner is the National Center for Missing and Exploited Children (NCMEC), which uses Videntifier’s technology to reduce the need for people to manually review harmful content.

Videntifier started from research at Reykjavik University and IRISA-CNRS and continues to use the latest advances in multimedia databases and computer vision in its work.

About Videntifier Technologies

Videntifier Technologies, founded in 2008 in Iceland, develops video identification tools to help organizations detect and manage illegal online content. Used by groups like NCMEC, its technology reduces manual review of harmful media. The company combines advanced research in multimedia databases and computer vision with a strong global partner network.