Whether you are an e-business with a streamlined data flow or an enterprise with large volumes of complex, unstructured data, you can always improve and streamline your existing search capabilities.
By seamlessly blending data knowledge into your search process, it becomes more intuitive, overarching and effective.
The scalability, efficiency and ease of integration expected from a modern search solution, are built in.
Your business deserves a lean and cost effective approach to modern search.
Garamond, our neural search engine is available on GitHub!
It makes it possible to create blazing fast, complex and scalable search and recommendation pipelines.
You can grab it from here. Happy hacking!
We build modern smart search solutions, either as a service (SaaS) or fully custom (code + data).
Our first product is Garamond, with full support for billion scale search and near real-time data stream indexing.
Vision
We want for everyone to be able to easily dive into large amounts of information, be it text, image, video, sound or just plain bytes.
We want to constantly develop and improve our work by evolving the search capabilities and adding P2P support.
We want to be part of the future of search.
Team
TECH
The core is based on Julia, MIT's own AI programming language.
Search solutions are virtualized and easily deployed using container technologies (e.g. Docker, Singularity).
Approach
Providing high quality search results in today's data environment is a very complex problem.
That's why we believe the only way to approach it is to be as lean and flexible as possible.
The solutions we build for our clients are tailored to easily complement or replace existing legacy search/recommendation engines.
Q: So, you're doing Artificial Intelligence?
A: Yes. Search is one of the fundamental building blocks in many AI systems.
Q: Are you providing AI consultancy services as well?
A: Yes, although our primary focus is search. If you like our work, drop us a line.
Q: Where can we find your work? Can we contribute?
A: Our code is freely available at https://github.com/OxoaResearch. You can contribute in any way you see fit (feature requests, issues, PRs)
Email :
Locations : Brussels - Belgium ,
Brasov - Romania