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Metadata
for AI workflows

Deasy Labs provides the best way to create and leverage metadata within your AI workflows

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How leading enterprises use Deasy Labs'  metadata workflow:

Direct connection to vector embeddings

We connect to any vector database and can generate metadata from both (i) embeddings or (ii) underlying documents

Auto-suggested metadata from your data

We model backward engineers the best metadata schema from your corpus of documents

Generate best-in-class multi-modal metadata at scale

We extract metadata at both chunk & document level, which is hierarchical, multi-modal and standardized

Use metadata for agent or node selection with our retrieval agent

Our retrieval agent uses the metadata to select the most relevant information and agents

Trusted by Leading Enterprises

Deasy Labs' metadata tagging solution for unstructured data has profoundly transformed our enterprise's knowledge management landscape. Their speed has allowed us to test the viability of our in-house AI product far quicker than expected, with their data preparation capability playing a critical step in the product workflow.

Sam Grice, CEO of Octopus Legacy (Financial Group)
Sam Grice
CEO of Octopus Legacy (Financial Group)

Deasy Labs' industry leading data governance and labeling capabilities have been invaluable in allowing us to achieve transformational automation and top line growth with speed to value, accuracy and reliability. Their team has been top notch in their technical and problem solving capabilities to enable this.

Beth Pollack, Applied AI and Data Strategy Operating Partner at Decision Science Advisors
Beth Pollack
Applied AI and Data Strategy Operating Partner, Decision Science Advisors

"What didn’t exist was a good approach for measuring data quality and relevance for unstructured data … Nobody was directly solving the issue of matching every generative AI use case with the ‘best’ possible set of data. Deasy Labs has developed novel approaches in this domain."

How it Works

Define metadata

Auto-suggested metadata
We analyse large document & image sets to auto-suggest the most relevant metadata for your use case

Customisable metadata
We enable anyone to easily define new metadata through LLM-powered labelling

Hierarchical metadata
We infer relationships between documents to build hierarchical metadata

Improve metadata

Auto-standardised
Automatic standardisation and grouping of similar metadata values to enable easy filtering and updates

Intelligently validated
Human-in-the-loop validation workflow to test, analyse and refine metadata through reinforcement learning

Traceable
Quality scores & evidence generated for all metadata to provide easy validation

Utilize metadata

Export & integrate
‍Direct connection of metadata back into underlying vector databases

Retrieve
Intelligent selection and filtering of the most relevant pieces of information

Maintain metadata
‍Continuous & automated maintenance of metadata, including dynamic taxonomies

Hierarchical metadata

Deasy Labs auto-detects relationships between metadata labels in order to build a hierarchical representation of the unstructured dataset. Hierarchical labels enable more efficient labelling, insight generation, and can be exported to enhance retrieval sequencing in AI applications.

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Diagram showing inferred hierarchy of metadata labels, including relationships between labels such as customer complaint, complaint type, general enquiry, and related factors like wait time and services used.

Built for seamless
enterprise deployment

Integrate with any data source (e.g., Sharepoint, S3, AzureBlob, Teams, Dropbox, … )

Deploy on-prem within your private cloud

Use Deasie as a platform or API''

Easy import and export of metadata to connect with your existing data systems & MDM tools

Auto-label tens of thousands of documents in rapid succession

Manage user permissions and controls

Download our report on the role of metadata in AI

Most companies are yet to realise the importance that high-quality metadata labels will play in the upcoming era of AI deployment. Download our report to get an in-depth analysis on the impact that metadata can have on building safe, scalable and accurate LLM applications.

Download Report
AI Deployment Report by Deasy Labs available for download, covering the role of metadata in AI