Unlock the Value of Unstructured Data
With the help of AI models, all data can be represented as a
vector.
Upload the vector embeddings to HIDDB to quickly find similarities
within your data set.
Image Search
Search by image and find similar pictures — think shopping for similar looking products. Combine with an NLP model to find images by search term.
Question Answering
Given a new question, e.g. originating from a chat, find semantically matching Q&As from a knowledgebase.
Recommender System
Recommend similar products, blog articles, books, movies — you name it. Display the results in e.g. your webshop or in your CRM.
Identity Verification
Use video, images, or audio to verify a person's identity; or search for similar faces or voices.
Material Research
Search for similar materials and predict material properties.
Audio Search
Search for similar songs, voices, bird sounds, or any other audio.
Quick and Easy Integration into Your Environment
HIDDB's REST API and SDKs for multiple programming languages make it easy and quick to integrate into production applications with just a few lines of code.
Manage on Your Terms
HIDDB is designed to be fully user-managed. Decide yourself how and where you want to deploy the database.
On top of that code is entirely Open-source, community driven and free-to-use.
Answers to Your Queries in the Blink of an Eye
Sub-10ms query latency and high recall rates at scale, even with billions of vectors and tens of thousands of queries per second.
Open-source code base written entirely in Rust.
Just Three Steps Away
Find an embedding model that works with your type of data. Use one of the many off-the-shelf models available or a self-developed model to transform your data into vector embeddings.
Upload your vector embeddings and metadata to HIDDB with the help of our SDKs or REST API. Full CRUD operations with live index updates and guaranteed persistence.
Find nearest neighbors to any vector embedding in < 10 ms with > 95% recall.
