See Komprise AI Preparation and Process Automation (KAPPA) data services examples and demonstration. Bring your custom data function. Komprise automates the rest.
Serverless Execution
Write a few lines of Python to define what to extract. Komprise provisions, scales, and executes the function across petabytes of file and object data with no infrastructure overhead.
Global Metadatabase
Every enriched tag feeds into the Komprise Global Metadatabase, making it instantly searchable with Deep Analytics and available for Smart Data Workflows and agentic AI pipelines.
Reusable Library
Komprise and its partners publish a growing library of pre-built data services that IT teams can configure for their specific requirements, covering industry-standard formats and enterprise-specific workflows.
Data Services Library
Each data service below shows a real KAPPA use case, the business problem it solves, and the key benefits for IT and data teams.
DICOM Header Extraction
DICOM files carry rich clinical metadata in their headers: patient ID, study type, scanner model, imaging protocol. The storage layer sees none of it. KAPPA extracts that context as searchable tags, making imaging datasets AI-ready without moving a single file.
- Filter CT and MRI datasets by clinical criteria for AI training
- Maintain HIPAA governance with PII tagging before AI ingest
- Preserve metadata as data moves across storage tiers
- Search imaging archives using real clinical criteria at scale
DICOM
FASTQ Metadata Extraction
Genomics pipelines generate petabytes of sequencing data in FASTQ format, designed for bioinformatics tool compatibility but not AI-scale analytics. KAPPA extracts sequencer metadata, quality scores, sample IDs, and project codes to enable precise dataset curation without disrupting research workflows.
- Identify and archive interim files from completed projects
- Filter low-quality reads before AI pipeline ingest
- Reduce genomics storage footprint with metadata-driven tiering
- Support population-scale research with unified metadata search
.bam
Image EXIF Metadata Extraction
Post-production workflows strip embedded metadata from digital media assets, severing context from content. KAPPA reads EXIF, XMP, and IPTC headers at ingest, preserving camera settings, rights information, and production context as persistent, searchable tags across your media storage estate.
- Restore lost production context from post-processed files
- Enforce rights and licensing metadata at petabyte scale
- Build AI-ready media catalogs with accurate content tags
- Search by shoot date, camera model, or rights status
XMP
IPTC
OSDU / LAS File Metadata Extraction
LAS (Log ASCII Standard) files store well log data across proprietary platforms, making cross-vendor discovery nearly impossible. KAPPA extracts OSDU-compliant metadata from LAS files, delivering vendor-neutral discoverability of subsurface data across the enterprise with no platform migration required.
- Search well logs across platforms without vendor lock-in
- Apply OSDU standard tags for enterprise-wide compliance
- Feed curated subsurface datasets to geoscience AI models
- Operate at scale without disrupting existing workflows
OSDU
More Data Services Coming
ESIF, ELN Metadata Extraction, PDF Metadata Extraction, and additional industry-specific data services are in development. Check back for new additions to this library.
Ready to Enrich Your Unstructured Data for AI?
See how KAPPA data services can extract the metadata your AI models need, in hours, not months.