Unstructured data governance for AI use cases
Unstructured data governance for AI use cases
An automated workflow to tag, filter and enrich unstructured content
Watch our webinars on using Deasy alongside leading AI companies
Watch our webinars on using Deasy alongside leading AI companies
Watch our webinars on using Deasy alongside leading AI companies
Partnering with leading companies on their unstructured data initiatives
Partnering with leading companies on their unstructured data initiatives
The best way to tag, filter and enrich unstructured data at scale
Data and AI teams use Deasy Labs' metadata workflow to build their underlying data foundation across all unstructured content
The best way to tag, filter and enrich unstructured data at scale
Data and AI teams use Deasy Labs' metadata workflow to build their underlying data foundation across all unstructured content
The best way to tag, filter and enrich unstructured data at scale
Data and AI teams use Deasy Labs' metadata workflow to build their underlying data foundation across all unstructured content
Auto-derived schemas & taxonomies
Reverse engineer domain-specific metadata tags and taxonomies without ANY input needed from business experts
Auto-derived schemas & taxonomies
Reverse engineer domain-specific metadata tags and taxonomies without ANY input needed from business experts
Auto-derived schemas & taxonomies
Reverse engineer domain-specific metadata tags and taxonomies without ANY input needed from business experts
Human-in-the-loop validation & fine-tuning
Test, validate and fine-tune all metadata through an easy human-in-the-loop testing studio
Human-in-the-loop validation & fine-tuning
Test, validate and fine-tune all metadata through an easy human-in-the-loop testing studio
Human-in-the-loop validation & fine-tuning
Test, validate and fine-tune all metadata through an easy human-in-the-loop testing studio
ACTION
Mark as correct
Mark as incorrect
Value: Bronze tier
Evidence: "Policy holders covered …"
ACTION
Mark as correct
Mark as incorrect
Value: Bronze tier
Evidence: "Policy holders covered …"
ACTION
Mark as correct
Mark as incorrect
Value: Bronze tier
Evidence: "Policy holders covered …"
Curate data slices
Leverage metadata to filter and curate relevant sets of files which can be rapidly served to end business or data science teams for their specific use case
Curate data slices
Leverage metadata to filter and curate relevant sets of files which can be rapidly served to end business or data science teams for their specific use case
Curate data slices
Leverage metadata to filter and curate relevant sets of files which can be rapidly served to end business or data science teams for their specific use case
METADATA
METADATA
METADATA
Export relevant metadata
Directly connect Deasy's metadata to file storage systems or vector databases for easy downstream consumption
Export relevant metadata
Directly connect Deasy's metadata to file storage systems or vector databases for easy downstream consumption
Export relevant metadata
Directly connect Deasy's metadata to file storage systems or vector databases for easy downstream consumption
EXPORTING
EXPORTING
EXPORTING
An end-to-end workflow to define, validate, extract and maintain metadata
An end-to-end workflow to define, validate, extract and maintain metadata
An end-to-end workflow to define, validate, extract and maintain metadata
Connect to unstructured data
Connect to either raw files or vector databases
Connect to unstructured data
Connect to either raw files or vector databases
Connect to unstructured data
Connect to either raw files or vector databases
AI-assisted schema generation
Auto-derive schemas tailored to your use cases with NO input from domain experts (or define tags yourself)
AI-assisted schema generation
Auto-derive schemas tailored to your use cases with NO input from domain experts (or define tags yourself)
AI-assisted schema generation
Auto-derive schemas tailored to your use cases with NO input from domain experts (or define tags yourself)
LLM-based tagging at scale
Extract ANY of tag from document chunks, with automatic synthesis to file-level metadata
LLM-based tagging at scale
Extract ANY of tag from document chunks, with automatic synthesis to file-level metadata
LLM-based tagging at scale
Extract ANY of tag from document chunks, with automatic synthesis to file-level metadata
Curate data slices
Filter millions of documents to find the most relevant subset for a given use case
Curate data slices
Filter millions of documents to find the most relevant subset for a given use case
Curate data slices
Filter millions of documents to find the most relevant subset for a given use case
Export and sync data
Directly export metadata with cloud storage systems or vector databases
Export and sync data
Directly export metadata with cloud storage systems or vector databases
Export and sync data
Directly export metadata with cloud storage systems or vector databases
Maintain metadata taxonomies
Automated maintenance and updates of taxonomies as data changes over time
Maintain metadata taxonomies
Automated maintenance and updates of taxonomies as data changes over time
Maintain metadata taxonomies
Automated maintenance and updates of taxonomies as data changes over time
Available as a user-friendly platform or a set of APIs
15%
Increase in retrieval accuracy from metadata
15%
Increase in retrieval accuracy from metadata
15%
Increase in retrieval accuracy from metadata
10k
Files tagged every 25 mins (assuming 75 page docs)
10k
Files tagged every 25 mins (assuming 75 page docs)
10k
Files tagged every 25 mins (assuming 75 page docs)
93%
Average metadata classification accuracy
93%
Average metadata classification accuracy
93%
Average metadata classification accuracy
Metadata to enhance RAG
Deasy's metadata orchestration is tailored towards optimizing retrieval workflows (through routing strategies and embedding enhancement)
Metadata to enhance RAG
Deasy's metadata orchestration is tailored towards optimizing retrieval workflows (through routing strategies and embedding enhancement)
Metadata to enhance RAG
Deasy's metadata orchestration is tailored towards optimizing retrieval workflows (through routing strategies and embedding enhancement)
Our enterprise customers demand scale, security and quality
Our enterprise customers demand scale, security and quality
Our enterprise customers demand scale, security and quality
Scalable tagging
Tag 1 million documents in less than a day with our robust & dynamically scaling infrastructure
Scalable tagging
Tag 1 million documents in less than a day with our robust & dynamically scaling infrastructure
Scalable tagging
Tag 1 million documents in less than a day with our robust & dynamically scaling infrastructure
Secure deployment
Deploy within your private cloud and host Deasy's open-source model in your private environment
Secure deployment
Deploy within your private cloud and host Deasy's open-source model in your private environment
Secure deployment
Deploy within your private cloud and host Deasy's open-source model in your private environment
Ongoing maintenance
Automated updates to metadata as data and business definitions evolve over time
Ongoing maintenance
Automated updates to metadata as data and business definitions evolve over time
Ongoing maintenance
Automated updates to metadata as data and business definitions evolve over time
Our metadata layer powers AI, cataloging & compliance use cases
Data & AI teams use Deasy Labs as their horizontal metadata capability to support a range of use cases
Our metadata layer powers AI, cataloging & compliance use cases
Data & AI teams use Deasy Labs as their horizontal metadata capability to support a range of use cases
Our metadata layer powers AI, cataloging & compliance use cases
Data & AI teams use Deasy Labs as their horizontal metadata capability to support a range of use cases
A managed metadata service for RAG
The easiest way to define, test and manage all the metadata that sits in your vector database
A managed metadata service for RAG
The easiest way to define, test and manage all the metadata that sits in your vector database
A managed metadata service for RAG
The easiest way to define, test and manage all the metadata that sits in your vector database
Building structured datasets for search
The quickest way to build a structured dataset from unstructured data to support search use cases (beyond RAG)
Building structured datasets for search
The quickest way to build a structured dataset from unstructured data to support search use cases (beyond RAG)
Building structured datasets for search
The quickest way to build a structured dataset from unstructured data to support search use cases (beyond RAG)
Enhancing retrieval performance
Auto-suggesting tailored metadata that can be embedded or used for routing to enhance speed & accuracy of retrieval
Enhancing retrieval performance
Auto-suggesting tailored metadata that can be embedded or used for routing to enhance speed & accuracy of retrieval
Enhancing retrieval performance
Auto-suggesting tailored metadata that can be embedded or used for routing to enhance speed & accuracy of retrieval
Curating data products for end consumers
A rapid way for enterprise data teams to curate "data slices" and serve this to business or data science teams
Curating data products for end consumers
A rapid way for enterprise data teams to curate "data slices" and serve this to business or data science teams
Curating data products for end consumers
A rapid way for enterprise data teams to curate "data slices" and serve this to business or data science teams
Feature engineering across unstructured data
Enabling data science teams to reverse engineer domain specific feature sets without input from domain experts
Feature engineering across unstructured data
Enabling data science teams to reverse engineer domain specific feature sets without input from domain experts
Feature engineering across unstructured data
Enabling data science teams to reverse engineer domain specific feature sets without input from domain experts
Sensitivity classification & cataloging
Highly scalable classification and tagging across all unstructured content for compliance & governance
Sensitivity classification & cataloging
Highly scalable classification and tagging across all unstructured content for compliance & governance
Sensitivity classification & cataloging
Highly scalable classification and tagging across all unstructured content for compliance & governance
Hear from our satisfied customers
Hear from our satisfied customers
Hear from our satisfied customers
Developed by award-winning team in enterprise software for AI and data governance.
Developed by award-winning team in enterprise software for AI and data governance.
Customized Plans for your needs
Customized Plans for your needs
Customized Plans for your needs
Free
Access Deasy's metadata SaaS product immediately
Connect to S3, Qdrant or Postgres
Auto-create or define any metadata
Extract metadata at scale
Use our API or platform
Enterprise
A white-glove approach for our enterprise customers to guarantee success with Deasy Labs.
Deployment in your private cloud
Infra to support millions of documents
Custom integrations into your AI & data pipelines
Hands-on support
Free
Access Deasy's metadata SaaS product immediately
Connect to S3, Qdrant or Postgres
Auto-create or define any metadata
Extract metadata at scale
Use our API or platform
Enterprise
A white-glove approach for our enterprise customers to guarantee success with Deasy Labs.
Deployment in your private cloud
Infra to support millions of documents
Custom integrations into your AI & data pipelines
Hands-on support
Free
Access Deasy's metadata SaaS product immediately
Connect to S3, Qdrant or Postgres
Auto-create or define any metadata
Extract metadata at scale
Use our API or platform
Enterprise
A white-glove approach for our enterprise customers to guarantee success with Deasy Labs.
Deployment in your private cloud
Infra to support millions of documents
Custom integrations into your AI & data pipelines
Hands-on support
"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."
"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."
Common questions — answered
Common questions — answered
Common questions — answered
What models do you use?
What models do you use?
What models do you use?
Can we use Deasy via API?
Can we use Deasy via API?
Can we use Deasy via API?
What do you mean by ‘metadata’?
What do you mean by ‘metadata’?
What do you mean by ‘metadata’?
How does Deasy validate the accuracy of the metadata?
How does Deasy validate the accuracy of the metadata?
How does Deasy validate the accuracy of the metadata?
What type of data do you support?
What type of data do you support?
What type of data do you support?
Can I bring my existing data dictionary into Deasy?
Can I bring my existing data dictionary into Deasy?
Can I bring my existing data dictionary into Deasy?
Do you chunk the underlying data before tagging?
Do you chunk the underlying data before tagging?
Do you chunk the underlying data before tagging?
What data connectors do you support?
What data connectors do you support?
What data connectors do you support?
How does your auto-suggested metadata functionality work?
How does your auto-suggested metadata functionality work?
How does your auto-suggested metadata functionality work?
Where is the data stored?
Where is the data stored?
Where is the data stored?
Does data leave our systems?
Does data leave our systems?
Does data leave our systems?
How does your pricing work?
How does your pricing work?
How does your pricing work?
Rethink your approach to metadata today
Start your free trial today and discover the significant difference our solutions can make for you.