Vendor-described product information. Availability, integrations and deployment must be validated during scoping. AI is optional roadmap for industrial pilots, not included MVP scope.
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R-DATAData & Analytics — Turn unstructured information into direction.
Turn unstructured information into direction.
Discuss a solutionRZC / R-DATACONNECTED SYSTEM
R-DATAData & Analytics
01AI metadata extraction
02Natural language processing
03Big data analytics
04Predictive insights
WHAT IT DOES
Make more of every data point.
An AI-powered metadata extraction and big data analytics platform that brings data management and predictive analysis together. Natural language processing, machine learning, and big data cloud computing help organizations extract metadata, analyze patterns, and turn information into actionable insights.
INSIDE R-DATAThe right tools.
The right tools.
In one place.
Purpose-built capabilities that work as part of a connected whole.
Natural language processing
Big data analytics
Predictive insights
Features
Automated metadata extraction
Identifies and organizes titles, dates, authors, categories, and keywords to reduce manual tagging.
Big data cloud integration
Supports data ingestion, storage, and analysis on scalable cloud infrastructure with dynamic resource allocation.
Predictive analytics and insights
Uses machine learning to uncover patterns in historical and incoming data, supporting proactive decisions.
Categorization and taxonomy management
Classifies documents and media into predefined or custom taxonomies, with multilingual processing and domain-specific ontologies.
AI-driven data enrichment
Adds context, fills missing fields, and recognizes people, locations, and organizations to make raw data more useful.
Incoming-data processing and automation
Automates metadata tagging, categorization, and content workflows as new data arrives.
Security and governance
Encryption, access controls, and audit trails support data protection and organizational governance.
Customizable, extensible architecture
Connects with existing systems and APIs, with customization for industry-specific requirements.
Benefits
More time for strategic work
Automates repetitive metadata tasks so teams can focus on strategic initiatives and creative work.
More consistent data
Consistent tagging helps reduce manual errors and improve searchability and data quality.
Room to scale
Cloud-native architecture and distributed processing support growing data volumes.
Evolving AI capabilities
Build data workflows around developments in AI, big data, and predictive analytics.
Use cases
Content management systems
Automates metadata tagging for digital assets to improve search, retrieval, and content workflows.
Research and academia
Organizes academic papers and research publications to support knowledge discovery.
Media and entertainment
Tags video, images, and audio with rich metadata for cataloging, retrieval, and content reuse.
Legal document review
Supports contract and legal-document analysis, risk monitoring, and accurate record keeping.
HOW WORK MOVESFrom first step
From first step
to what comes next.
01Ingest data
02Extract metadata
03Analyze patterns
04Forecast outcomes
SEE IT IN ACTIONClick through the work.
Click through the work.
Watch it flow.
Pick a workflow to see how RZC moves it forward — step by step, with every record connected.
PURCHASE REQUEST PR-3081LIVE
Committed spend this week€48,200
- 1Request raised
- 2Budget checked
- 3Manager approved
- 4PO sent to supplier
- 5Invoice matched
Stainless valves ×120Nordic Steel Oy
€14,400Packaging filmBaltic Pack
€6,850Lab reagentsScandi Lab
€2,190 Invoice matched
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