MonoQwen-VisionLightOn
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troveGENIntellara Technologies
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Related Products
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About
MonoQwen2-VL-v0.1 is the first visual document reranker designed to enhance the quality of retrieved visual documents in Retrieval-Augmented Generation (RAG) pipelines. Traditional RAG approaches rely on converting documents into text using Optical Character Recognition (OCR), which can be time-consuming and may result in loss of information, especially for non-textual elements like graphs and tables. MonoQwen2-VL-v0.1 addresses these limitations by leveraging Visual Language Models (VLMs) that process images directly, eliminating the need for OCR and preserving the integrity of visual content. This reranker operates in a two-stage pipeline, initially, it uses separate encoding to generate a pool of candidate documents, followed by a cross-encoding model that reranks these candidates based on their relevance to the query. By training a Low-Rank Adaptation (LoRA) on top of the Qwen2-VL-2B-Instruct model, MonoQwen2-VL-v0.1 achieves high performance without significant memory overhead.
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About
troveGEN is a retrieval-augmented generation (RAG) and document-search platform for teams building AI products and organizations that need governed access to internal information. It ingests files, scanned documents, web pages and connected sources, then parses, OCRs, chunks, indexes and retrieves relevant passages with hybrid search, reranking, filters and access controls. Applications and AI agents can use its REST API, TypeScript SDK or Model Context Protocol server to search content and receive source-linked results; optional answer generation supports cited responses. Customers can use managed hosting or connect their own vector database, models and content sources, including air-gapped deployments. Use cases include internal knowledge search, customer support, technical documentation, and document workflows across finance, healthcare, legal and government.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Companies working with visually rich documents requiring a solution to enhance retrieval accuracy and efficiency in OCR-free RAG systems
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Audience
AI product developers and organizations that need searchable, governed access to unstructured documents and knowledge, including engineering, HR, legal, healthcare, and financial-services teams.
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Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and VideosNo images available
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
$25/month
troveGEN-Z Launch costs $25/month and includes 1,500 pages, 8,000 searches, 1,500 answers, and two projects. Annual billing costs 10 times the monthly price. The one-time free trial includes 500 pages, 2,000 searches, and 200 answers. Sovereign deployments are quoted.
Free Version
Not Supported
Free Trial
Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationLightOn
Founded: 2016
France
www.lighton.ai/lighton-blogs/monoqwen-vision
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Company InformationIntellara Technologies
Founded: 2025
India
troveGEN.com
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Alternatives |
AlternativesNo Alternatives
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Categories |
Categories |
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Integrations
Amazon S3
Not Supported
Azure Blob Storage
Not Supported
Cohere
Not Supported
Google Drive
Not Supported
Microsoft SharePoint
Not Supported
Model Context Protocol (MCP)
Not Supported
OpenAI
Not Supported
Pinecone
Not Supported
Qdrant
Not Supported
pgvector
Not Supported
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Integrations
Amazon S3
Supported
Azure Blob Storage
Supported
Cohere
Supported
Google Drive
Supported
Microsoft SharePoint
Supported
Model Context Protocol (MCP)
Supported
OpenAI
Supported
Pinecone
Supported
Qdrant
Supported
pgvector
Supported
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