We Create The Most Realistic Artificial Intelligence

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi finibus at mauris eu sollicitudin que venenatis.
Robust
Fast integration, support larger variety of data type:
  • OpenAPI v3 documentation
  • Support for strings, geo-locations, and other data types.
Accurate
Maintain index integrity even with multiple filters:
  • Custom implementation of HNSW index preventing accuracy degradation (TBP)
Distributed (TBD)
Most reliable for large scale deployment:
  • Distributed consensus algorithm with no single point of failure (TBP)
Optimized
Search index tuning enables effective query execution:
  • Dynamic query planning
  • Payload data indexing
  • Vector quantization (TBP)

It's Free and Open Source

Get started by downloading a pre-build Docker Image - it is only 35Mb!

docker pull generall/qdrant

Take a look a tour through our [Quick Start Guide]
or build your first neural search wit out step-by-step [Tutorial]

Use Cases and Examples For Your Business

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi finibus at mauris eu sollicitudin. Maecenas a imperdiet
libero, ac congue orci. Pellentesque et erat id leo tincidunt aliquam.
  • Neural
    Text Search
  • Image Search -
    food discovery
  • Recommendations
    with conditions

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi finibus at mauris eu sollicitudin. Maecenas a imperdiet libero, ac congue orci.

  • WHAT: Replace old-school text search with modern neural-based approach. Use semantic embeddings instead of keywords.
  • WHY: Increase search recall, allow users to search even for short texts with which no keywords match.
  • HOW: With pre-trained neural network and Qdrant vector search engine
Demo Tutorial Source Code

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi finibus at mauris eu sollicitudin. Maecenas a imperdiet libero, ac congue orci.

  • WHAT: Build a visual food discovery application. Search food nearby
  • WHY: Creates a new approach to discover restaurants and cafes. Enables a whole new dimension of food discovery
  • HOW: With pre-trained ResNet154 + Qdrant recommendation API + Qdrant geo-filters.
Demo Tutorial Source Code

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi finibus at mauris eu sollicitudin. Maecenas a imperdiet libero, ac congue orci.

  • WHAT: Suggest an additional goods based on client interactions - purchases, viewed pages or other activities
  • WHY: Increase basket size, sell more shit
  • HOW: Train custom LightFM + Qdrant recommendation API
Demo Tutorial Source Code

Who uses Qdrant?

Our Latest Articles

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi finibus at mauris eu sollicitudin. Maecenas a im-
perdiet libero, ac congue orci. Pellentesque et erat id leo tincidunt aliquam.
Metric Learning
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi finibus at mauris eu sollicitudin ac congue orci.
Learn More
Vector Search Tutorial
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi finibus at mauris eu sollicitudin ac congue orci.
Learn More
Filterable HNSW
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi finibus at mauris eu sollicitudin ac congue orci.
Learn More
0+

Successful Projects

0+

Professional Experts

0+

Happy Customers

0+

Happy Customers

Get in touch

Not sure how Qdrant can be useful for you? Ask us!