Updated April 2026 · USPTO PatentsView
Information Storage Patent Landscape
243 patents tracked across 4 companies in CPC G11.
The Information Storage technology class (CPC G11) covers 243 U.S. patents tracked here, held across 4 companies. Filing activity, top patent holders, and recent grants below all come directly from USPTO records.
Patent landscape for Information Storage technology (CPC class G11). Covers innovations in information storage from leading companies worldwide.
Information Storage at a Glance
243 patents under Information Storage make this a focused mid-tier technology class. Mid-tier classes often have a clear top-three of corporate patent holders, with the long tail filled by specialist firms and university tech-transfer offices.
IBM (108 patents, grade B), Microsoft (73, grade C), and Nvidia (48, grade D) hold the top three positions in Information Storage. The grade column reflects each company's overall Patent Strength Score across its full portfolio, not just patents in this technology class.
Patent Activity by Year
Filing activity in Information Storage has accelerated, with the most recent five years averaging about 11 new patents per year — roughly 32% above the earlier window. Acceleration often correlates with a technology shift attracting fresh corporate R&D, and it tends to push expiration cliffs further out as new filings replace older ones.
Recent Patents in Information Storage
| Patent # | Title | Assignee | Granted | Expires | Claims | Status |
|---|---|---|---|---|---|---|
| 10000064 | Data storage system with efficient graphene architecture | IBM | Aug 3, 2028 | Sep 11, 2044 | 42 | 18.4y left |
| 10000088 | Apparatus for scalable data encoding in nano-scale systems | IBM | Jun 6, 2028 | Jun 21, 2044 | 28 | 18.2y left |
| 10000461 | Computer-implemented method for dynamic quantum optimization | Microsoft | Apr 1, 2028 | Jan 13, 2044 | 20 | 17.8y left |
| 10000397 | Apparatus for distributed computational operations in CMOS environments | Microsoft | Feb 8, 2028 | Oct 18, 2044 | 24 | 18.5y left |
| 10000111 | Computer-implemented method for integrated RF optimization | IBM | Jan 18, 2028 | Mar 1, 2044 | 19 | 17.9y left |
| 10000419 | Method for optimized wireless communication using 5G | Microsoft | Dec 12, 2027 | Feb 3, 2043 | 49 | 16.8y left |
| 10000453 | Method for integrated digital information retrieval | Microsoft | Nov 26, 2027 | Jul 16, 2044 | 20 | 18.3y left |
| 10000457 | Data storage system with integrated neural architecture | Microsoft | Nov 20, 2027 | Aug 4, 2044 | 7 | 18.3y left |
| 10000097 | System for advanced signal transmission in graphene networks | IBM | Oct 26, 2027 | Jan 9, 2044 | 20 | 17.8y left |
| 10000127 | Apparatus for low-latency data encoding in RF systems | IBM | Oct 6, 2027 | Feb 19, 2043 | 13 | 16.9y left |
| 10000534 | Data storage system with optimized blockchain architecture | Intel | Aug 7, 2027 | May 26, 2044 | 8 | 18.1y left |
| 10000465 | System for adaptive neural network processing with lidar | Microsoft | Aug 5, 2027 | Jun 10, 2044 | 16 | 18.2y left |
| 10000546 | Data storage system with modular 5G architecture | Intel | Feb 21, 2027 | May 9, 2043 | 12 | 17.1y left |
| 10000371 | Computer-implemented method for scalable digital optimization | Microsoft | Feb 15, 2027 | Jun 9, 2043 | 36 | 17.2y left |
| 10000469 | Data storage system with low-latency AI-driven architecture | Microsoft | Jan 11, 2027 | Aug 22, 2044 | 25 | 18.4y left |
| 10000446 | Method for dynamic RF information retrieval | Microsoft | Jan 5, 2027 | Jun 27, 2044 | 6 | 18.2y left |
| 10000452 | Method for optimized nano-scale information retrieval | Microsoft | Dec 13, 2026 | Dec 11, 2043 | 29 | 17.7y left |
| 10000076 | Method for advanced analog information retrieval | IBM | Dec 3, 2026 | Oct 17, 2043 | 32 | 17.5y left |
| 10000412 | Apparatus for modular data encoding in MEMS systems | Microsoft | Nov 16, 2026 | Jun 27, 2042 | 25 | 16.2y left |
| 10000087 | System for enhanced signal transmission in digital networks | IBM | Oct 8, 2026 | Mar 22, 2044 | 40 | 18.0y left |
What Expirations Mean for Information Storage
As patents in Information Storage expire, the underlying methods and apparatuses enter the public domain. Competitors gain freedom to operate without licensing the original claims, and downstream products incorporating the formerly protected technology can ship without a royalty stack. This is the ground-truth mechanism that drives generic-drug economics and the broader competitive dynamics in semiconductor process generations and consumer electronics platforms.
For pharmaceutical and biotech CPC classes, drug-specific exclusivities tracked in the FDA Orange Book can delay generic entry past patent expiration. For non-drug technology classes, expiration is a cleaner trigger — competitors generally gain freedom-to-operate immediately. Either way, the underlying expiration math comes from USPTO records.
How This Patent Landscape Is Built
Patents are assigned to Information Storage based on their primary CPC classification (G11) as recorded by USPTO examiners. Total counts include all patents in the tracked dataset that carry this CPC prefix; recent-patent and yearly-trend tables are derived from the same record set. Each company\'s grade reflects its overall Patent Strength Score across its entire tracked portfolio, not just patents in this CPC class. Read the full methodology for the data pipeline, score weights, and known limitations.
Frequently Asked Questions
What is the Information Storage CPC class?
Information Storage corresponds to Cooperative Patent Classification (CPC) prefix G11, the international system used by the USPTO and EPO to organize patents by technical subject matter. Patent landscape for Information Storage technology (CPC class G11). Covers innovations in information storage from leading companies worldwide. CPC classes are assigned by patent examiners and update as the technology evolves, so the patent set tracked here reflects the current classification of every included patent.
Who are the top patent holders in Information Storage?
IBM (108 patents), Microsoft (73 patents), Nvidia (48 patents), Intel (14 patents) are the leading holders in Information Storage. Patent counts at the company level are useful for spotting concentration, but they do not tell you about claim strength — for a finer signal, see each company's Patent Strength Score grade in the table below.
How many Information Storage patents will expire soon?
Per-year expiration counts for this technology class can be derived from the recent patents table on this page combined with each patent's expiration date — patents typically expire 20 years from earliest non-provisional filing. For year-by-year expiration totals across all CPC classes, see the expiring-year pages on this site, which break down each year's cohort by company and technology.
What happens when patents in Information Storage expire?
When a patent expires, its claims enter the public domain. For Information Storage, that means competitors can implement the underlying methods or apparatus without licensing fees. The practical impact varies — in regulated areas like pharmaceuticals, FDA-granted exclusivities can extend market protection past patent expiry. In unregulated technology areas, expiration usually translates directly into freedom-to-operate for new entrants.
Where does Information Storage patent data come from?
All patent data is sourced from the U.S. Patent and Trademark Office through the PatentsView and Open Data Portal APIs. CPC classifications are assigned by USPTO examiners and are part of the official patent record. Verify any individual patent through USPTO Patent Public Search (ppubs.uspto.gov) or Google Patents.
Sources: U.S. Patent and Trademark Office (PatentsView, Open Data Portal). Public-domain federal data. Cite as: "PatentCliff, Information Storage landscape, April 2026. Data: USPTO."
Last updated 2026-04-10 · 243 patents tracked in Information Storage.