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ease
features
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support

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Description

Pinecone Rerank V0 is a cross-encoder model specifically designed to enhance precision in reranking tasks, thereby improving enterprise search and retrieval-augmented generation (RAG) systems. This model processes both queries and documents simultaneously, enabling it to assess fine-grained relevance and assign a relevance score ranging from 0 to 1 for each query-document pair. With a maximum context length of 512 tokens, it ensures that the quality of ranking is maintained. In evaluations based on the BEIR benchmark, Pinecone Rerank V0 stood out by achieving the highest average NDCG@10, surpassing other competing models in 6 out of 12 datasets. Notably, it achieved an impressive 60% increase in performance on the Fever dataset when compared to Google Semantic Ranker, along with over 40% improvement on the Climate-Fever dataset against alternatives like cohere-v3-multilingual and voyageai-rerank-2. Accessible via Pinecone Inference, this model is currently available to all users in a public preview, allowing for broader experimentation and feedback. Its design reflects an ongoing commitment to innovation in search technology, making it a valuable tool for organizations seeking to enhance their information retrieval capabilities.

Description

Ragie simplifies the processes of data ingestion, chunking, and multimodal indexing for both structured and unstructured data. By establishing direct connections to your data sources, you can maintain a consistently updated data pipeline. Its advanced built-in features, such as LLM re-ranking, summary indexing, entity extraction, and flexible filtering, facilitate the implementation of cutting-edge generative AI solutions. You can seamlessly integrate with widely used data sources, including Google Drive, Notion, and Confluence, among others. The automatic synchronization feature ensures your data remains current, providing your application with precise and trustworthy information. Ragie’s connectors make integrating your data into your AI application exceedingly straightforward, allowing you to access it from its original location with just a few clicks. The initial phase in a Retrieval-Augmented Generation (RAG) pipeline involves ingesting the pertinent data. You can effortlessly upload files directly using Ragie’s user-friendly APIs, paving the way for streamlined data management and analysis. This approach not only enhances efficiency but also empowers users to leverage their data more effectively.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
Cohere
Confluence
Google Cloud Platform
Hugging Face
Instill
LangChain
Langtrace
Microsoft OneDrive
Nango
New Relic
Nexla
Notion
Pinecone
PowerPoint
Pulumi
Snowflake
TruLens
TwelveLabs
Unstructured

Integrations

Amazon Web Services (AWS)
Cohere
Confluence
Google Cloud Platform
Hugging Face
Instill
LangChain
Langtrace
Microsoft OneDrive
Nango
New Relic
Nexla
Notion
Pinecone
PowerPoint
Pulumi
Snowflake
TruLens
TwelveLabs
Unstructured

Pricing Details

$25 per month
Free Trial
Free Version

Pricing Details

$500 per month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Pinecone

Founded

2019

Country

United States

Website

www.pinecone.io/blog/pinecone-rerank-v0-announcement/

Vendor Details

Company Name

Ragie

Founded

2024

Website

www.ragie.ai/

Product Features

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