Companies file H-1Bs and PERMs under different legal entity names, making data analysis unreliable. Immigration law firms, HR tech platforms, and researchers waste significant time manually resolving these entity relationships.
An API and data product that maintains a curated mapping of corporate entity relationships across DOL filings — linking subsidiaries, DBAs, and parent companies. Uses SEC filings, corporate registrations, and crowdsourced corrections to build the entity graph.
Subscription API pricing based on usage tiers ($200-2000/mo). Enterprise licensing for immigration software platforms that want to embed the data.
The pain is real but narrow. Immigration attorneys and researchers genuinely waste hours on manual entity resolution. The Reddit thread demonstrates the frustration clearly — GM filing 537 H-1Bs but zero PERMs is likely an entity fragmentation artifact, not reality. However, this is a 'paper cut' pain for most users, not a 'hair on fire' emergency. Law firms work around it manually. The pain intensifies for platforms trying to build reliable analytics at scale.
This is a niche within a niche. ~12,000 immigration attorneys in the US, maybe 200 immigration-focused tech platforms, a few hundred corporate immigration teams at large employers, and a small researcher community. Realistic TAM is likely $5-15M/year for a standalone API product. At $200-2000/mo per customer, you need 200-500 paying customers to hit $1M ARR, which is achievable but represents significant market penetration in a small pool.
Law firms and corporate teams already spend heavily on immigration data and tools ($500-5000/mo for case management). $200-2000/mo is within budget. However, entity resolution alone may feel like a 'nice to have' rather than a must-have — it enhances existing workflows but doesn't replace them. Enterprise licensing to platforms (Envoy, immigration SaaS) is the stronger revenue path, but sales cycles will be 3-6 months. Policy researchers often have limited budgets.
A solo dev can build an MVP in 6-8 weeks. DOL disclosure data is publicly available (OFLC). SEC EDGAR filings are programmatically accessible. Basic entity matching (fuzzy string matching, EIN cross-referencing, known alias tables) gets you 60-70% accuracy. The hard part is the long tail — ambiguous entities, state-level DBA lookups, and maintaining accuracy over time. The 'crowdsourced corrections' piece adds complexity. NLP/ML entity linking raises the bar. MVP is feasible; production-grade accuracy is a multi-year moat-building exercise.
This is the strongest signal. Nobody is selling immigration-specific entity resolution as a standalone product. D&B and OpenCorporates don't touch DOL filings. Immigration platforms don't do cross-employer entity mapping. Free tools are literal string matchers. The gap is wide open because the market is too small for D&B to care about and too data-intensive for law firms to solve in-house. Classic 'too niche for big players, too specialized for generalists' territory.
Strong subscription fit. DOL filings happen quarterly/annually, entity relationships change through M&A, and accuracy improves over time. Customers need ongoing access, not one-time lookups. API metered pricing is natural. The data depreciates if not maintained — new filings, new subsidiaries, reorgs — which creates genuine recurring need, not artificial lock-in.
- +Wide open competitive gap — literally nobody sells this specific product
- +Strong recurring revenue dynamics with API subscription model
- +Data moat deepens over time — accuracy and coverage compound
- +Clear potential acquirers/embedders (Envoy, immigration SaaS platforms)
- +Public data sources (DOL, SEC) reduce data acquisition costs
- +Regulatory complexity and political scrutiny around H-1B create sustained demand for better data
- !Small TAM ceiling — may be a solid lifestyle business ($500K-2M ARR) but unlikely to be a venture-scale outcome without expanding scope
- !Entity resolution accuracy is deceptively hard — 70% accuracy is easy, 95% is a multi-year grind, and customers may not tolerate errors in legal/compliance contexts
- !Sales cycle to law firms and enterprise immigration teams is slow and relationship-driven — not a self-serve PLG motion
- !Government could improve DOL data quality or add employer identifiers (EIN standardization), eliminating the need overnight
- !Crowdsourced corrections model requires critical mass of users who are also willing to contribute — chicken-and-egg problem
Legal research platforms that aggregate immigration case data and DOL filings, allowing searches across PERM and H-1B databases
Free or freemium tools that let users search H-1B and PERM LCA disclosure data by employer name, job title, and salary
Top immigration law firms that maintain proprietary internal databases of employer filing patterns and entity relationships as part of their practice
General-purpose corporate entity resolution and hierarchy databases. D&B maps parent-subsidiary relationships globally. OpenCorporates aggregates public corporate registrations.
Immigration case management platforms for employers and law firms, handling H-1B, PERM, and other visa workflows end-to-end
Start with the top 500 H-1B/PERM employers by filing volume. Ingest DOL OFLC disclosure data, cross-reference with SEC EDGAR subsidiary lists, and build a manually-curated entity graph for these top filers. Ship as a simple REST API: input an employer name from a DOL filing, get back the resolved parent company and all known filing aliases. Include a confidence score. Add a web UI for browsing and a feedback button for corrections. Focus on accuracy for Fortune 500 companies where entity fragmentation is worst and most valuable to resolve.
Free tier (10 lookups/day, top 100 employers only) to attract researchers and validate demand → Paid API ($200/mo for 1000 lookups, full coverage) for law firms and analysts → Enterprise licensing ($1000-5000/mo) for immigration SaaS platforms embedding the data into their products → Premium data feeds with historical entity mapping and M&A tracking for compliance teams → Potentially expand into broader employer intelligence (office locations, salary benchmarking by true parent company)
8-12 weeks to first dollar. 4-6 weeks to build MVP with top 500 employer coverage. 2-4 weeks to land first paying customer through direct outreach to immigration attorneys active on forums like Reddit, VisaJourney, and immigration law listservs. First enterprise platform deal likely 4-6 months out.
- “'Stanford almost certainly files PERMs under The Leland Stanford Junior University' — entity fragmentation is a known unsolved problem”
- “'If their PERM process routes through a different entity name, you'd want to know which one' — clear demand for entity resolution”