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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Cohere Compass serves as a smart enterprise search and discovery platform that links agents and models with business data, equipping AI applications with essential context via robust search and retrieval capabilities. Employing sophisticated extraction techniques along with AI-driven indexing, it effectively identifies and presents pertinent information from enterprise documents with remarkable precision. The system is designed to be multimodal, multilingual, and agnostic to formats, enabling it to comprehend various types of documents, including images, slides, spreadsheets, PDFs, DOCX, and XLSX files. Furthermore, it can integrate with existing data sources or allow for local document uploads, automatically processing, indexing, and managing that information without the need for teams to maintain or scale their own vector database infrastructure. Built on Cohere’s Embed and Rerank retrieval models, Compass not only supports AI agents and retrieval-augmented generation applications but also facilitates a cohesive approach to enterprise knowledge search, enhancing collaboration and decision-making across the organization. Its versatility and efficiency make it an invaluable tool for businesses aiming to leverage their data effectively.

Description

MonoQwen2-VL-v0.1 represents the inaugural visual document reranker aimed at improving the quality of visual documents retrieved within Retrieval-Augmented Generation (RAG) systems. Conventional RAG methodologies typically involve transforming documents into text through Optical Character Recognition (OCR), a process that can be labor-intensive and often leads to the omission of critical information, particularly for non-text elements such as graphs and tables. To combat these challenges, MonoQwen2-VL-v0.1 utilizes Visual Language Models (VLMs) that can directly interpret images, thus bypassing the need for OCR and maintaining the fidelity of visual information. The reranking process unfolds in two stages: it first employs distinct encoding to create a selection of potential documents, and subsequently applies a cross-encoding model to reorder these options based on their relevance to the given query. By implementing Low-Rank Adaptation (LoRA) atop the Qwen2-VL-2B-Instruct model, MonoQwen2-VL-v0.1 not only achieves impressive results but does so while keeping memory usage to a minimum. This innovative approach signifies a substantial advancement in the handling of visual data within RAG frameworks, paving the way for more effective information retrieval strategies.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

GitHub Yes 
Gmail Yes 
Google Drive Yes 
Jira Yes 
Linear Yes 
Microsoft Exchange Yes 
Microsoft OneDrive Yes 
Microsoft Outlook Yes 
Microsoft SharePoint Yes 
Model Context Protocol (MCP) Yes 
Notion Yes 
Salesforce Yes 
Slack Yes 

Integrations

GitHub No 
Gmail No 
Google Drive No 
Jira No 
Linear No 
Microsoft Exchange No 
Microsoft OneDrive No 
Microsoft Outlook No 
Microsoft SharePoint No 
Model Context Protocol (MCP) No 
Notion No 
Salesforce No 
Slack No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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

Customer Support

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

Types of Training

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

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Cohere AI

Founded

2019

Country

Canada

Website

cohere.com/compass

Vendor Details

Company Name

LightOn

Founded

2016

Country

France

Website

www.lighton.ai/lighton-blogs/monoqwen-vision

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