Processing layers
4
Ingestion, normalization, aggregation, and publishing define the core pipeline.
Methodology
How raw public records become usable sponsorship intelligence.
WorkVisaInsights processes public immigration and labor datasets into normalized, aggregated pages that make employer, role, salary, and location patterns easier to evaluate.
Trust snapshot
Built for source transparency, clear boundaries, and fast research.
Pipeline shape
Collect → Clean → Aggregate
Metric style
Summaries over public records
Future roadmap
Visa Score framework
Metric posture
Transparent
Metrics are summaries of public records, not predictions or private signals.
Quality checks
Ongoing
Entity normalization and record aggregation improve as source files evolve.
Processing
Data pipeline
The platform keeps dataset identity visible while creating consistent research surfaces.
Pipeline stage
Collect source files
Public DOL and USCIS files are loaded by dataset and year while preserving source fields where practical.
Pipeline stage
Normalize entities
Employer names, job titles, worksites, states, wages, and dates are standardized for search and comparison.
Pipeline stage
Aggregate metrics
Records are grouped into employer, job, location, salary, and trend views using consistent dataset-specific keys.
Pipeline stage
Publish fast pages
Aggregated results power static or cached pages so users can scan sponsor signals quickly.
Metrics
How metrics are calculated
Most metrics are aggregate summaries over public records, not predictions or legal determinations.
Filing volume
Counts records by dataset, employer, fiscal year, job title, worksite, and other available dimensions.
Salary and wage measures
Uses disclosed wage fields to calculate medians, ranges, and comparisons where sufficient records exist.
Approval and decision rates
Calculated only where public source files include petition or case outcome fields.
Aggregation
How entities are grouped
Most pages are powered by consistent grouping keys, then rendered as fast summary surfaces.
- Employer aggregates
- Normalized employer names are grouped to summarize filings, wages, roles, locations, and outcome signals.
- Role aggregates
- Job titles and SOC fields help cluster similar work so users can compare demand and compensation.
- Location aggregates
- State and city fields are grouped to power regional sponsor and salary intelligence.
- Time aggregates
- Fiscal year and filing date fields support trend pages and refresh status views.
Visa Score placeholder
A future Visa Score may combine sponsorship volume, wage strength, approval consistency, recency, and market concentration. It should be treated as a research aid, not legal advice or a guarantee of filing success.
- Score inputs must be explainable and visible to users.
- Low-volume employers should be handled cautiously to avoid false precision.
- Legal and source-data disclaimers should remain close to score interpretation.
- The score should supplement, not replace, raw filing and salary context.
Quality posture
The platform should continue improving entity normalization, duplicate handling, source-file compatibility, and field-level documentation as new public releases become available.
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