Digital Thread Patents: Who Leads, Where the Gaps Are 2026
- Three assignees hold the entire ranked field. The top 3 and top 5 combined both cover 100% of the 16 records in scope — there is no long tail yet, only a leader and two much smaller filers.
- Filing peaked in 2024 at 12 records, then softened. Growth from a flat 2022 midpoint of 2 records to a 2024 peak looks like a single filing wave rather than a sustained ramp, and the partial 2026 count of 1 will rise as later filings publish.
- AI-based computing already touches half the field. G06N appears in 50.0% of the 16 records alongside core G06F digital-data-processing claims (93.8%), while additive manufacturing and robotics classes sit at just 12.5% each — a sign of where claim density is still thin.
What this landscape covers
This landscape tracks patent filings at the intersection of digital thread architecture and engineering data continuity — the mechanisms that keep design, simulation, manufacturing and test data linked across a product’s lifecycle. The search combines model-based definition and traceability language with IPC codes for simulation/CAE (G06F30), enterprise data management (G06Q10) and information retrieval (G06F16), producing a tightly scoped set of 16 published records.
Because the field is small and recent, family-level counting and raw document counting converge here; there is little continuation filing to strip out. Publication lags filing by roughly 18 months, so the 2025-2026 window in every trend chart understates true filing activity.
Filing trend and technology composition
Sixteen records, filed between 2015 and mid-2026, form the entire scope of this landscape. The trend and class breakdown below use that same denominator throughout.
A single filing wave, not a steady climb
Filings sat at zero in 2017, stayed low through a 2022 midpoint of 2 records, then jumped to a peak of 12 in 2024. The partial 2026 figure of 1 record is an artefact of publication lag, not a real slowdown yet — but the shape through 2024 already looks like one concentrated push rather than compounding growth.
Core data processing dominates; adjacent classes are thin
G06F (electric digital data processing) appears in 93.8% of records and G06N (AI-based computing) in 50.0%, confirming that most filings frame digital thread work as a software and modeling problem. G05B (control systems, 31.3%) and H04L (digital transmission, 18.8%) show up as supporting infrastructure, while B25J (robotics), B29C (plastics shaping) and B33Y (additive manufacturing) each sit at just 12.5% — physical-execution linkages that are claimed far less densely than the data-layer itself.
Shares are the percentage of the 16 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Digital Thread and Engineering Data Continuity with Eureka
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Try EurekaThe most-cited records in this dataset
WO2025064639A1 — Platform-enabled orchestration and optimization of digital workflows
Systems and methods for optimizing a digital workflow within a digital platform are provided. An illustrative method includes generating, based on a user request, a decentralized digital thread associated with the digital workflow, and generating a workflow data structure based on the decentralized digital thread. The method also includes calculating a workflow cost associated with executing one or more workflow tasks of the workflow data structure, and identifying a cost-reducing modification to the workflow data structure. Finally, the method includes generating an updated workflow data structure and a corresponding updated decentralized digital thread based on the identified modification.Filed by Istari Digital, the current leader by filing count, and cited 4 times within this dataset.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US12380418B2 | Adaptive additive manufacturing for value chain networks | 8 |
| 2 | WO2025064639A1 | Platform-enabled orchestration and optimization of digital workflows | 4 |
| 3 | US20250284488A1 | System and Methods for Generating Models and Digital Threads using Graphs | 2 |
| 4 | WO2025030057A1 | Machine learning engine for workflow enhancement in digital workflows | 1 |
Citation counts favour older records in any searched corpus; treat them as a signal of influence within this dataset, not as a ranking of current technical importance.
Publication numbers are shown where the record carries one (4 of 4 rows); clicking a row searches Eureka by that number.
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With only 16 records and three ranked assignees, this is an early-stage claim landscape where positioning now matters more than benchmarking against a crowded incumbent field.
No long tail yet
The top 3 and top 5 combined both account for all 16 records in scope, meaning every published filing in this dataset traces to one of three organisations. There is no fragmented field of small independent filers to track — the near-term competitive question is what these three do next, not who else enters.
One wave, not a trend line
Activity rose from a flat midpoint of 2 records in 2022 to a peak of 12 in 2024, then dropped to a partial count of 1 in 2026. That pattern reads as a concentrated filing push around a specific product or program rather than compounding annual growth, and later years will fill in as publication catches up.
AI framing is already standard
Half of all records in scope carry an AI-computing classification (G06N) alongside core data-processing claims (G06F, 93.8%), showing that digital thread filings are increasingly framed as AI-assisted workflow or model-generation systems rather than plain data-management tools.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to digital thread and engineering data continuity, with the prior art for and against each one.
Who holds the field, and where it is thin
The ranked field here is genuinely small: three assignees, one clear leader, and receiving-office activity split evenly across four jurisdictions.
Istari Digital sets the pace
Istari Digital holds the leading position in this ranking and is also the only one of the three ranked assignees still filing in the most recent year, giving it both scale and current momentum in a field where the other two show no latest-year activity.
Momentum is uneven across the three
One ranked assignee shows a full year-over-year drop to zero latest-year filings, while a second also records zero in the latest year. Only the leader shows any latest-year activity, which concentrates near-term filing risk and opportunity around a single organisation.
Evenly split across four offices
Receiving-office activity is split evenly at 4 filings apiece across Australia, the European Patent Office, the United States and the WIPO PCT route, indicating these applicants are pursuing multi-jurisdiction coverage from early in the program rather than favouring a single home market.
| Assignee | Recent year | YoY |
|---|---|---|
| ISTARI DIGITAL INC | 1 | — |
| Qiangli Value Chain Network Portfolio 2019 Co., Ltd. | 0 | — |
| PREWITT RIDGE INC | 0 | -100% |
Where to take this analysis
This dataset is small enough to read in full, but that also means its early signals are worth tracking closely as more filings publish.
Watch the 2025-2026 publication window
The partial 2026 count will rise as filings from the leader and any new entrants clear the roughly 18-month publication lag; re-check the trend before concluding the 2024 peak was a one-off.
Explore filing trends in EurekaMap the under-claimed physical-execution classes
Robotics, additive manufacturing and plastics-shaping classes each sit at 12.5% of records — well below the AI and core data-processing classes — and are worth a closer claim-by-claim read before filing there.
Run a white space search in EurekaTrack the leader's next moves closely
With one assignee holding 13 of 16 records and the only active latest-year filings, its next publications are the single largest signal available in this field.
Monitor assignee activity in EurekaCommon questions about digital thread patents
In this dataset, only three assignees appear in the ranked field, and together they account for all 16 records in scope — the top 3 and top 5 combined both reach 100% of the field. That means there is no fragmented long tail of small filers to monitor yet; competitive tracking here is really about watching three organisations rather than scanning a crowded market. This is typical of an early-stage technology area where claim space is still being staked out.
Filing rose from a flat midpoint of 2 records in 2022 to a peak of 12 records in 2024, but then the partial 2026 figure drops to 1 — which looks more like a single concentrated filing push than a steady growth trend. Because publication lags filing by roughly 18 months, the most recent one to two years will always look artificially low, so it is too early to call the 2024 peak a plateau or a decline. Anyone using this trend for planning should revisit it once the 2025-2026 window has fully published.
Core electric digital data processing (G06F) appears in 93.8% of the 16 records, and AI-based computing (G06N) appears in exactly half, showing that most filings treat digital thread systems as software and modeling problems with an increasing AI component. Business and enterprise data processing (G06Q) and control systems (G05B) show up as supporting layers. Physical-execution classes — robotics, additive manufacturing, plastics shaping — each sit at only 12.5% of records, marking them as comparatively open ground.
WO2025064639A1, filed by Istari Digital, describes generating a decentralized digital thread from a user request, building a workflow data structure from it, calculating the cost of executing workflow tasks, and then identifying and applying a cost-reducing modification that produces an updated digital thread. In practice this is a claim over cost-optimized workflow orchestration built on a digital thread data structure, rather than over digital threads generally. It is cited 4 times within this dataset, making it one of the more referenced records in the set.
The clearest gaps sit in classes that appear in the dataset but at far lower density than the core data-processing classes: additive manufacturing (B33Y), robotics (B25J) and plastics shaping (B29C) each cover only 12.5% of the 16 records, compared with 93.8% for core data processing. That gap suggests the physical as-built linkage side of the digital thread — connecting design and simulation data to actual manufacturing execution — is claimed far less densely than the software and AI-modeling layer, and is worth a closer look before assuming the space is occupied.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.