How it Works

A best-in-class approach for leveraging metadata within RAG

Deasy Labs’ platform provides an intelligent and efficient approach for enterprises to rapidly define, extract and include metadata within their RAG applications.

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Step 1

Generate relevant metadata

Deasy Labs' metadata creation process is designed to be derive bespoke metadata from your documents, geared towards RAG optimization.

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Diagram showing the metadata creation features by Deasy Labs, including verifiable, auto-suggested, multi-modal, customisable, hierarchical, and auto-standardised metadata generation

Diagram showing metadata refinement process by Deasy Labs, including label quality scoring, label precision, and human-in-the-loop enhancements

Step 2

Refine & test metadata

Our metadata refinement workflow leads to high-quality, standardised metadata that are customised to your business and always up-to-date.

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Step 2

Refine & test metadata

Our metadata refinement workflow leads to high-quality, standardised metadata that are customised to your business and always up-to-date.

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Step 3

Utilize metadata

Our Retrieval Agent has been designed to intelligently assess metadata in order to find the most relevant nodes for a given query.

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Diagram showing metadata utilization process by Deasy Labs, including embedded metadata, direct export, and integration with MDM tools

Best-in-class

Deasy Labs combines best-in-class models with a user-assisted workflow and interface, empowering you to curate, prepare and connect unstructured data to AI applications

Certified

SOC-2 Certified Security Assurance

Ensuring your data protection and compliance with industry-standard security controls

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