
Qdrant
Powering the next generation of AI applications with advanced and high-performant vector similarity search technology.
USD | 2022 | 2023 |
---|---|---|
Revenues | 0000 | 0000 |
% growth | - | 175 % |
EBITDA | 0000 | 0000 |
Profit | 0000 | 0000 |
EV | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x |
R&D budget | 0000 | 0000 |
Source: Dealroom estimates
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Qdrant is a tech startup that specializes in providing AI solutions to leading companies. The company's primary offering is a vector database and similarity search engine, which is essentially a tool that allows for the efficient search of high-dimensional vectors, or complex data sets. This technology is particularly useful for engineers who are looking to turn neural network encoders into applications for matching, searching, recommending, and more.
Qdrant's business model is based on deploying its technology as an API service, which means it provides its software to other businesses for integration into their own systems. This is a popular model in the tech industry as it allows for high scalability and flexibility in terms of cost and resource allocation. The company's technology is developed in Rust language, a programming language known for its performance and safety, particularly in systems programming.
The company's technology is also cloud-native and scales horizontally, meaning it can handle increasing amounts of data without compromising on performance. This makes it an attractive solution for businesses dealing with large amounts of data.
Qdrant's technology can be applied in a variety of ways. For example, it can be used to find similar images, detect duplicates, or even find a picture based on a text description. This makes it a versatile tool for businesses in a range of industries.
In terms of revenue, Qdrant likely makes money by charging businesses for the use of its API service. The exact pricing model is not specified, but it's common for companies in this space to charge based on the amount of data processed or the number of API calls made.
Keywords: AI Solutions, Vector Database, Vector Similarity Search Engine, API Service, High-Dimensional Vectors, Scalability, Rust Language, Cloud-Native, Image Recognition, Text Search.