What is Metarank?
Metarank is an open-source ranking service. It can help you to build a personalized semantic/neural search and recommendations.
If you just want to get started, try:
- a Collaborative Filtering recommendations guide to create a "you may also like" widget as seen on many e-commerce stores.
With Metarank, you can make your existing search and recommendations smarter:
- Integrate customer signals like clicks and purchases into the ranking - and optimize for maximal CTR!
- Use LLMs in bi- and cross-encoder mode to make your search understand the true meaning of search queries.
Metarank is fast:
- optimized for reranking latency, it can handle even large result sets within 10-20ms. See benchmarks.
- as a stateless cloud-native service (with state managed by Redis), it can scale horizontally and process thousands of RPS. See Kubernetes deployment guide for details.
Save your development time:
- Metarank can compute dozens of typical ranking signals out of the box: CTR, referer, User-Agent, time, etc - you don't need to write custom ad-hoc code for most common ranking factors. See the full list of supported ranking signals in our docs.
- There are integrations with many possible streaming processing systems to ingest visitor signals: See data sources for details.
Metarank helps you build advanced ranking systems for search and recommendations:
- Semantic search: use state-of-the-art LLMs to make your Elasticsearch/OpenSearch understand the meaning of your queries
- Recommendations: traditional collaborative-filtering and new-age semantic content recommendations.
- Learning-to-Rank: optimize your existing search
Blog posts: