KAPPA Data Services
Serverless Compute for Unstructured Data
Bring your custom data function. We automate the rest.
Komprise AI Preparation & Process Automation (KAPPA)
Unlimited Custom Data Operations Possibilities
From healthcare and life sciences to media, professional services and manufacturing, users can get exactly the data they need and not what they don’t.
Industry
Healthcare
Media & Entertainment
Legal, Corporate
Research, Exploration, Design
KAPPA Data Services
DICOM Header Extraction
BAM Metadata Extraction
Electronic Lab Notebook (ELN) Metadata Extraction
Media Image info extraction (EXIF, XMP, IPTC, etc.)
Media Order Metadata Extraction
PDF metadata extraction MS Purview tag synchronization
ERP, Salesforce, Costs, Budget ID, Project Info Extraction
Why is Flexible Extraction Important?
Most healthcare organizations customize medical metadata to fit their research and compliance
Media metadata is often lost post-processing when saved in compact formats.
Sensitive data labels consistent with corporate standards
Each organization has different ways of tracking information related to a project/initiative
Easily Define & Execute Custom Data Actions
Komprise serverless compute architecture executes Kappa functions with zero user intervention.
- Add Python script for per-file operations across hybrid storage silos.
- Komprise handles infrastructure provisioning and executing across large data sets.
- Complete complex data operations jobs in hours, not months unlike legacy ETL connectors and plug-ins.
Global Search & Curation
The Komprise Global Metadatabase extends the life of enriched metadata for AI.
- New custom metadata created from KAPPA functions is easy to find and reuse in the Komprise Global Metadatabase service.
- Data scientists and researchers can search metadata by keyword to curate precise data.
- Access a developing library of reusable data services from Komprise.
Ready to get started with KAPPA Data Services?
Get custom metadata for any need with a plug-and-play process.
Streamline Agentic AI Data Orchestration
Agentic AI workflows can directly invoke KAPPA functions for their data needs.
- An airline’s customer service AI agent tags all files for a journey with its reservation number using a KAPPA function.
- A grant-writing AI agent prepares prior art by using ERP project codes to find prior relevant research proposals.
- A M&A execution AI agent uses Active Directory SIDs to propose segmentation of a company’s data into post-divestiture units.
Dig Deeper
Blog
A Serverless Approach to Metadata Enrichment
Better metadata is not only a pathway to more accurate, relevant AI outcomes but also lower costs…
Press Release
Komprise Accelerates Agentic AI with Serverless Compute for Unstructured Data
KAPPA data services allow rapid development of custom data functions.
Frequently Asked Questions
What is KAPPA?
Komprise AI Preparation & Process Automation (KAPPA) data services are a serverless compute offering for unstructured data, included in the Komprise Intelligent Data Management platform. With KAPPA, IT can rapidly deliver custom data services, such as industry-specific metadata extraction, without having to provision or manage the infrastructure to process the operation across large datasets. Automate unstructured data discovery, classification, tagging, and zero-move ingestion to AI pipelines, fueling better insights, lower costs, and faster outcomes. What makes Komprise unique is that you have a global view and orchestration of all your data across silos, even as data moves or infrastructure changes.
Why do enterprises need KAPPA?
AI needs high-quality unstructured data which requires rich metadata enrichment through data tagging, which supplies structure and identifying traits to the data. The challenge enterprises face is that the metadata for unstructured data is often contextual and specific to their enterprise, their industry and their security constraints.
How is KAPPA better than current methods for custom data operations?
Custom metadata extraction has typically been handled with ETL and other traditional approaches of data processing using pre-built connectors and plug-ins. These methods are time-consuming, inflexible, and costly to maintain. Creating just one custom data operation for an AI data workflow could take months.
Ready to Deliver the Right Data to AI?
Schedule a call with our unstructured data management experts and we’ll review Komprise Smart Data Workflow use cases.
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