Best Neural Search Software for OpenLIT
View:
Compare the Top Neural Search Software that integrates with OpenLIT as of October 2025
Sort By:
This a list of Neural Search software that integrates with OpenLIT. Use the filters on the left to add additional filters for products that have integrations with OpenLIT. View the products that work with OpenLIT in the table below.
What is Neural Search Software for OpenLIT?
Neural search software is a type of artificial intelligence technology that uses deep learning algorithms to help users find relevant information. It works by understanding the user's query and analysis language, context, and relationships between data points. Neural search is becoming more popular due its ability to provide fast and accurate results. The technology has numerous potential applications across a variety of industries. Compare and read user reviews of the best Neural Search software for OpenLIT currently available using the table below. This list is updated regularly.
-
1
Cohere
Cohere AI
Cohere is an enterprise AI platform that enables developers and businesses to build powerful language-based applications. Specializing in large language models (LLMs), Cohere provides solutions for text generation, summarization, and semantic search. Their model offerings include the Command family for high-performance language tasks and Aya Expanse for multilingual applications across 23 languages. Focused on security and customization, Cohere allows flexible deployment across major cloud providers, private cloud environments, or on-premises setups to meet diverse enterprise needs. The company collaborates with industry leaders like Oracle and Salesforce to integrate generative AI into business applications, improving automation and customer engagement. Additionally, Cohere For AI, their research lab, advances machine learning through open-source projects and a global research community.Starting Price: Free -
2
Qdrant
Qdrant
Qdrant is a vector similarity engine & vector database. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more! Provides the OpenAPI v3 specification to generate a client library in almost any programming language. Alternatively utilise ready-made client for Python or other programming languages with additional functionality. Implement a unique custom modification of the HNSW algorithm for Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results. Support additional payload associated with vectors. Not only stores payload but also allows filter results based on payload values.
- Previous
- You're on page 1
- Next