Data Architecture
How the Intelligence Infrastructure Works
Vivameda operates a multi layer workforce intelligence infrastructure that transforms hundreds of millions of professional records into validated, analysis-ready intelligence products.
This layered architecture ensures consistency, comparability, and analytical depth across millions of companies, enabling use cases that are not possible with flat or unstructured datasets. Primary coverage focuses on the United States, with additional signals across major global markets.
Architecture
Five Layers of Intelligence
Raw Data Sources
Consolidated professional records from multiple global datasets. Licensed source material is aggregated at scale, forming the foundation of the intelligence infrastructure.
Hundreds of millions of professional records across 100+ countries.
Entity Resolution Layer
Company entities are normalized and deduplicated into stable company identifiers. This layer resolves naming variations, mergers, and subsidiary structures into a unified entity graph.
Thousands of companies resolved into unique, stable identifiers.
Master Company Index
A unified database of companies with standardized attributes such as industry classification, geographic headquarters, company size banding, and founding year. This index serves as the reference layer for all downstream products.
Standardized firmographic attributes across the full company universe.
Company Year Intelligence Layer
Company snapshots capturing workforce size, growth rate, role composition, and seniority distribution for each year. This layer structures the data as longitudinal company-year observations, enabling multi-year trend analysis and workforce evolution tracking.
Company-year observations spanning 1950 to 2020.
Derived Intelligence Signals
Higher level analytical signals computed from the company year layer. These include hiring velocity, workforce composition changes, scaling stage indicators, and organizational restructuring patterns.
Analytical signals designed for investment research, strategy, and AI modeling.
Structure
How the Data is Structured for Analysis
All data is anchored on a consistent company-year key, forming the foundation of the entire system.
Growth signals, workforce structure, and capability data are aligned on the same temporal model, allowing seamless cross-layer analysis.
Each layer is connected through a unified identity structure, ensuring that companies, roles, and capabilities can be analyzed together without additional preprocessing or manual joins.
Instead of delivering isolated datasets, the system is designed as a connected analytical model. This allows users to move from company growth to workforce structure to capabilities within a single framework.
Observed data gets enriched with current headcount, skills, capabilities, and financial information
Analytical Views
Ready-to-Use Analytical Views
The system includes pre-structured views designed for immediate analysis:
Company Profile View
Unified company-year dataset with growth and structural signals.
Role-Ready View
Filtered dataset optimized for workforce structure analysis.
Capability Buckets
Stable, aggregated representation of company capabilities.
Validation
Data Validation and Structural Integrity
This overview outlines how the dataset is structured, validated, and prepared for analytical use across growth, workforce, and capability layers.
Source Data Scale
The Workforce Intelligence Training Ground
1.2 TB
Structured Workforce Archive
48M+
Observed Company-Year Records
4.2M+
Companies Across Layers
1.8B+
Skill-Level Signals
90%+
Analytical Layer Signal Coverage
70+
Years of Historical Depth
From Infrastructure to Intelligence Products
The datasets available on this site are workforce intelligence products generated from the architecture described above. Each dataset represents a specific analytical window within the broader intelligence infrastructure, selected where company coverage and data density are strongest. Each product represents a specific access layer to the full intelligence system, from foundational growth signals to complete capability-level analysis.
This means every dataset benefits from the full depth of the infrastructure: entity resolution, standardized taxonomies, multi year temporal alignment, and derived analytical signals.
Infrastructure
Enterprise Grade Data Residency
With a focus on structured, compliant, and business-ready intelligence. Our approach prioritizes clarity, consistency, and responsible data structuring, making the datasets easy to use while maintaining high standards.
Tier 3 Data Center
Hosted in Helsinki, Finland. Redundant power, cooling, and network connectivity.
EU Data Standards
Data processed and stored within the EU. Full EU data residency with structured compliance workflows.
Delivery Formats
Structured delivery in CSV, Parquet, Snowflake, and RAG file with documented schemas.
Access Control
Role based access controls, audit trails, and encrypted storage at rest and in transit.