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features
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support

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Description

Achieve exceptional response quality through a vector database specifically designed for advanced retrieval augmented generation (RAG) and contemporary search functionalities. Emphasize substantial growth with a robust, enterprise-ready vector database that inherently includes security, compliance, and ethical AI methodologies. Create superior applications utilizing advanced retrieval techniques that are underpinned by years of research and proven customer success. Effortlessly launch your generative AI application with integrated platforms and data sources, including seamless connections to AI models and frameworks. Facilitate the automatic data upload from an extensive array of compatible Azure and third-party sources. Enhance vector data processing with comprehensive features for extraction, chunking, enrichment, and vectorization, all streamlined in a single workflow. Offer support for diverse vector types, hybrid models, multilingual capabilities, and metadata filtering. Go beyond simple vector searches by incorporating keyword match scoring, reranking, geospatial search capabilities, and autocomplete features. This holistic approach ensures that your applications can meet a wide range of user needs and adapt to evolving demands.

Description

RankLLM is a comprehensive Python toolkit designed to enhance reproducibility in information retrieval research, particularly focusing on listwise reranking techniques. This toolkit provides an extensive array of rerankers, including pointwise models such as MonoT5, pairwise models like DuoT5, and listwise models that work seamlessly with platforms like vLLM, SGLang, or TensorRT-LLM. Furthermore, it features specialized variants like RankGPT and RankGemini, which are proprietary listwise rerankers tailored for enhanced performance. The toolkit comprises essential modules for retrieval, reranking, evaluation, and response analysis, thereby enabling streamlined end-to-end workflows. RankLLM's integration with Pyserini allows for efficient retrieval processes and ensures integrated evaluation for complex multi-stage pipelines. Additionally, it offers a dedicated module for in-depth analysis of input prompts and LLM responses, which mitigates reliability issues associated with LLM APIs and the unpredictable nature of Mixture-of-Experts (MoE) models. Supporting a variety of backends, including SGLang and TensorRT-LLM, it ensures compatibility with an extensive range of LLMs, making it a versatile choice for researchers in the field. This flexibility allows researchers to experiment with different model configurations and methodologies, ultimately advancing the capabilities of information retrieval systems.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Azure AI Services Yes 
Azure Machine Learning Yes 
Azure Marketplace Yes 
Azure OpenAI Service Yes 
Cognee Yes 
Gemini No 
Gemini Enterprise No 
Llama No 
Microsoft Azure Yes 
Microsoft Copilot Studio Yes 
Microsoft Foundry Agent Service Yes 
Microsoft Intelligent Data Platform Yes 
Mistral AI No 
NVIDIA TensorRT No 
OpenAI No 
Python No 
Qwen No 
RankGPT No 
Titan CMS Yes 

Integrations

Azure AI Services No 
Azure Machine Learning No 
Azure Marketplace No 
Azure OpenAI Service No 
Cognee No 
Gemini Yes 
Gemini Enterprise Yes 
Llama Yes 
Microsoft Azure No 
Microsoft Copilot Studio No 
Microsoft Foundry Agent Service No 
Microsoft Intelligent Data Platform No 
Mistral AI Yes 
NVIDIA TensorRT Yes 
OpenAI Yes 
Python Yes 
Qwen Yes 
RankGPT Yes 
Titan CMS No 

Pricing Details

$0.11 per hour
Free Trial Yes 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/products/ai-services/ai-search/

Vendor Details

Company Name

Castorini

Country

Canada

Website

github.com/castorini/rank_llm/

Product Features

Enterprise Search

AI / Machine Learning No 
Faceted Search / Filtering No 
Full Text Search No 
Fuzzy Search No 
Indexing No 
Text Analytics No 
eDiscovery No 

Product Features

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Alternatives

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