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Platform and trust guideUnified product and data reference

How WorkVisa Insights works

WorkVisa Insights turns public U.S. visa and labor-certification disclosures into a research product you can actually navigate. Start with raw datasets when you need detail, move into 360 modules when you need synthesis, and keep the data-source context visible throughout.

Official dataset families

3

LCA, H-1B, and PERM public disclosures

Platform structure

4

Explore, Intelligence, Tools, and Insights

360 modules

2

Employer 360 and Location 360

Research posture

Search-first

Built for comparison, not static reporting

Public-data foundation

LCA, H-1B, and PERM remain the system of record behind every employer, location, job, and wage surface.

Research, not advice

The product helps you compare sponsor markets and filing behavior. It does not replace legal counsel or agency determinations.

One connected workflow

The strongest use case is moving from datasets into `Employer 360`, `Location 360`, and compensation tools without losing context.

Who It Helps

Built for faster immigration research

The platform is designed for people comparing sponsors, roles, wages, and markets under uncertainty. The product shell prioritizes quick scanning, cross-links, and consistent definitions.

Job seekers

Compare sponsor quality, salary posture, and location strength before committing time to an application.

Immigration teams

Benchmark employers, filings, and green-card depth with one surface instead of separate public spreadsheets.

Market researchers

Track location, employer, and occupation shifts across LCA, H-1B, and PERM with consistent normalization.

Product Structure

The navigation follows the research workflow

Instead of flattening every route into one long menu, the product is organized by the kind of work you are doing: raw exploration, synthesized intelligence, support tools, and editorial context.

Intelligence

Intelligence

Cross-dataset intelligence modules built to evaluate sponsor quality and market opportunity fast.

Insights

Insights

Editorial analysis, market commentary, and narrative updates tied back to the product data.

Data Foundation

Every major surface rolls back to the same three disclosure systems

The datasets stay separate where raw disclosure detail matters, but the platform connects them when users need a unified employer or location view.

LCA

LCA Intelligence

Labor Condition Application Intelligence

Analyze LCA filings, wage benchmarks, and filing outcomes across employers, jobs, and locations.

U.S. Department of Labor

Labor Condition Application disclosure dataset

Fiscal Years 2015-2026

H1B

H1B Intelligence

H1B Petition Intelligence

Explore petition approvals, denials, employer filing behavior, and worksite concentration in one place.

U.S. Citizenship and Immigration Services

USCIS Form I-129 public disclosure dataset

Fiscal Years 2015-2026

PERM

PERM Intelligence

PERM Labor Certification Intelligence

Understand permanent labor certification signals across employers, locations, processing, denials, and the green-card pipeline.

U.S. Department of Labor

PERM labor certification public dataset

Fiscal Years 2008-2026

Trust Model

What we do to keep the product usable

Public immigration disclosures are valuable but messy. The platform improves usability through normalization, consistent route structure, and explicit limits on what the data can and cannot tell you.

Official public sources

Every dataset on the platform starts from public U.S. government disclosures rather than private estimates.

Normalized entities

Employer naming, compensation units, and location values are standardized so cross-year comparisons are usable.

Research-ready workflows

The product layers raw dataset exploration with 360 modules, salary tools, and connected navigation paths.

Clear usage boundaries

This is a research platform, not legal advice. Filing disclosures do not guarantee visa issuance or future outcomes.

Next Step

Need the deep dataset reference?

Use About Data for source systems, field dictionaries, cleaning logic, disclosure caveats, and the methodology context behind public u.s. government datasets.