Question: I need a customizable platform that allows me to fine-tune ranking models for my specific e-commerce use case.

If you want a customizable foundation to train your own ranking models for your e-commerce application, Shaped is a strong contender. It includes real-time adaptation based on behavioral signals, a library of pre-trained LLMs and neural ranking models you can fine-tune, and customizable ranking and retrieval components. The platform also offers explainable results with in-session analytics and performance metrics, which makes it well-suited for optimizing buyer-seller interactions and improving the user experience. Shaped's enterprise-grade security and scalability meet GDPR and SOC2 requirements and offers white-glove support and direct integration with data sources.

Another good option is Algolia, an AI-infused search infrastructure that blends keyword search with vector understanding and dynamic re-ranking based on user behavior and trends. It also offers personalization and AI synonyms, and it's good for e-commerce and other industries, with a pay-as-you-go pricing model. Algolia's documentation, integrations and API clients in several languages and frameworks make it easy for developers to get started.

For a real-time recommender service, Recombee offers a scalable service that uses AI personalization to boost user engagement and sales. It's got a RESTful API and SDKs for easy integration and includes real-time analytics and insights. Customers can control the recommendation engine with custom filters and boosters, so it's a good tool for optimizing KPIs through AI-powered A/B testing.

Last, HawkSearch offers an AI-infused e-commerce search service that includes concept search in multiple languages, image search and smart autocomplete. It integrates with several e-commerce platforms like Adobe and Shopify, and it can help improve user experience and conversions through personalized recommendations and product comparisons.