USPTO TSDR API Documentation
Explore TSDR case identifiers, record retrieval and authorized access requirements.
Learn more →People often use “trademark database” to mean several different things: a search system used to discover marks, a record system used to inspect a case, or a structured dataset built for analysis or outreach. Those are different products.
USPTO Trademark Search is a discovery/search layer. TSDR is a record-level status and document layer. A professional commercial dataset is a third layer: a defined set of records normalized and qualified for a particular business question.
| Layer | Primary purpose |
|---|---|
| Trademark Search | Find and filter federal trademark records. |
| TSDR | Inspect current status and documents for a known application/registration. |
| Raw export | Machine-readable or spreadsheet output from a source/search; may still need interpretation and cleanup. |
| Qualified dataset | Records selected under explicit rules, normalized, verified and structured for the target use case. |
When you already know a case identifier, the TSDR API supports programmatic status and document checks, separate from keyword discovery and commercial lead datasets.
Explore TSDR case identifiers, record retrieval and authorized access requirements.
Learn more →Choose the correct system for your particular research task.
Learn more →For commercial data, inclusion logic, freshness, provenance and field interpretation can matter more than the raw number of rows. A smaller correctly qualified cohort may be more useful than a massive unfiltered dump.
For commercial data, inclusion logic, freshness, provenance and field interpretation can matter more than the raw number of rows. A smaller correctly qualified cohort may be more useful than a massive unfiltered dump.
A search system is optimized for discovery. A record system is optimized for case-level inspection. A commercial dataset is optimized for repeatable analysis, segmentation or operations. Confusing those layers creates bad expectations—for example, assuming that a search export is already deduplicated, that every visible email is a verified owner contact, or that one broad status flag is enough to define a prospect.
For AI and data workflows, a qualified dataset should make the semantics explicit: which source supplied each important field, which field drove inclusion, when the record was checked, and which transformations or exclusions were applied. That semantic layer is what turns a collection of rows into reusable intelligence.
No. Trademark Search is the current federal search system; TSDR is the record-level status and document system.
A raw export can be useful, but it usually does not encode the full business qualification rules, provenance, deduplication and field interpretation required for a professional use case.
Yes, subject to the customer’s lawful use and data-governance requirements. Explicit field definitions and provenance make downstream analysis more reliable.
| Need | Best-fit layer |
|---|---|
| Find a trademark record | Use a discovery/search database such as the current USPTO Trademark Search system. |
| Verify a specific case | Use record-level status/document evidence such as TSDR. |
| Analyze a defined cohort | Use a structured dataset with explicit status/event, date and qualification fields. |
| Repeat the same commercial filter | Use a documented qualification profile and deduplication rule rather than a one-off manual search. |
| Audit why a row was included | Retain identifiers, provenance and verification metadata with the delivered data. |
Tell us the business question, not just “send the database.”