Metarank

Metarank is an open-source ranking service designed to enhance search and recommendation systems. It enables developers to integrate customer signals, personalize results in real-time, and leverage large language models (LLMs) for semantic understanding. As an open-source alternative to platforms like AWS Personalize and Tecton, Metarank offers greater transparency, flexibility, and control over data and deployment.

Key features include:

• Semantic Neural Search: Utilizes state-of-the-art LLMs to improve search accuracy.
• Recommendations: Supports trending and similar-item recommendations using collaborative filtering.
• Personalization: Employs secondary reranking (LambdaMART) for personalized search results.
• AutoML: Offers automatic feature generation and model retraining.
• A/B Testing: Facilitates A/B testing through multiple model serving.

Use cases:

• E-commerce: Powering "you may also like" widgets and personalized product recommendations.
• Search Engines: Improving search result relevance by incorporating user behavior and semantic understanding.
• Content Discovery: Enhancing content recommendations based on user preferences and trending topics.