Text Watermarking Patents: Who Leads, Where the Gaps Are 2026
Text Watermarking and Detection Patents: Who Leads and Where the Field Is Still Open
41.3% concentration. The top 5 of 100 ranked assignees hold 74 of 179 records in scope (41.3%), with a long tail of single- and few-filing entrants behind them. Filings peaked in 2017 at 12 and have moved unevenly since; the complete-year comparison of 2021 (4) to 2024 (7) shows a 75% rise, the clearest read on current direction given the 18-month publication lag.
- 1HALLIBURTON ENERGY SERVICES INC35
- 2MONSANTO TECHNOLOGY LLC13
- 3DIGITAL MEDICAL EXPERTS10
- 4STEVENS INSTITUTE OF TECHNOLOGY8
- 5THALES SA8
See the full text watermarking and detection analysis in Eureka
- The complete ranking, not just the top five
- Every IPC branch with its share of the corpus
- The most-cited records, and where claim space is still thin
Common questions on text watermarking patents
How concentrated is the text watermarking and detection patent field?
It is moderately concentrated at the top and thin below it. Five assignees hold 41.3% of the 179 records in scope, and the top 10 combined hold 58.7%. Below the top 10, the ranked list of 100 companies thins quickly into entrants with only one or a handful of filings each, which is typical of a field still forming its core claim boundaries rather than one dominated by a settled oligopoly.
Is patent filing activity in text watermarking growing or slowing?
On the most recent complete years, filing activity is growing: 2021 to 2024 saw filings rise from 4 to 7, a 75% increase. Filings in 2025 and 2026 appear lower in the raw count, but that reflects the roughly 18-month lag between filing and publication rather than a real drop, so those years should not be read as a slowdown. 2017 remains the single highest-filing year on record at 12.
Which patent classes matter most for text watermarking claims?
G06F, covering electric digital data processing, is the largest single class at 21.8% of the 179 records, followed by G06T image data processing at 16.2%, with G06K text recognition and G06N AI-model computation each near 7-8%. The dataset’s search string also pulls in older signal-detection classes such as G01V, G01S and E21B from geophysical and industrial sensing prior art, because those fields share the same statistical-detection and threshold language used in text watermark detection claims.
Disclaimer. This analysis is based on Patsnap Eureka data drawn from a limited snapshot of global patent records and is provided for general information and reference only. Patent data carries inherent limitations — recent filings are under-counted because of publication lag, counts may be on a record or family basis, classification and applicant-name data may contain errors or duplicates, and the underlying search query defines the scope shown — so the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing here is an exhaustive prior-art, novelty, freedom-to-operate or validity search, nor does it constitute legal, financial or professional advice, and it should not be relied upon as such. Verify independently and review with qualified patent and legal professionals before acting on it.
Method: Filing trend and technology composition. Derived from a Patsnap search on Text Watermarking and Detection covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish. Every share divides by all records in scope. Data: Patsnap Eureka. See the full landscape report.