Prosecution Insights
Prosecution Insights
5 pending office actions • 1 client • 5 examiners • 4 art units • 0 of 5 (0%) have an AI response strategy ready • 2 patents granted in the last 365 days
Based on the USPTO statutory response window for each pending office action. 2 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §103 only | 5 (100%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| DANG, HUNG Q | 1 | 68.4% | +18.2% |
| CHEN, YU | 1 | 67.9% | +29.6% |
| HUTCHESON, CODY DOUGLAS | 1 | 64.3% | +52.3% |
| SHAH, SAYED MUNEER | 1 | — | — |
| PRESTON, ASHLEY DAWN | 1 | 43.7% | +27.6% |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 4 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18438946 | GENERATING AND PROVIDING VISUAL CONTENT ITEMS FOR DISPLAY | CHEN, YU | 26d overdue |
| 18505398 | TECHNIQUES FOR CONTENT RECOMMENDATION IN MULTIMEDIA ENVIRONMENTS | PRESTON, ASHLEY DAWN | 9d |
| 18597099 | GENERATION OF MEDIA SEGMENTS FROM LARGER MEDIA CONTENT FOR MEDIA CONTENT NAVIGATION | DANG, HUNG Q | — |
| 18423789 | USING A LARGE LANGUAGE MODEL TO IMPROVE TRAINING DATA | HUTCHESON, CODY DOUGLAS | — |
| Client (Assignee) | Pending OAs |
|---|---|
| ROKU, INC. | 5 |
| Art Unit | Apps |
|---|---|
| 2484 | 1 |
| 2613 | 1 |
| 2659 | 1 |
| 3689 | 1 |
| App # | Title | Client | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|---|
| 18597099 | GENERATION OF MEDIA SEGMENTS FROM LARGER MEDIA CONTENT FOR MEDIA CONTENT NAVIGATION | Roku, Inc. | DANG, HUNG Q | 2484 | §103 | Non-Final OA | — | Pending | Mar 06, 2024 |
| 18438946 | GENERATING AND PROVIDING VISUAL CONTENT ITEMS FOR DISPLAY | Roku, Inc. | CHEN, YU | 2613 | §103 | Final Rejection | 26d overdue | Pending | Feb 12, 2024 |
| 18423789 | USING A LARGE LANGUAGE MODEL TO IMPROVE TRAINING DATA | Roku, Inc. | HUTCHESON, CODY DOUGLAS | 2659 | §103 | Final Rejection | — | Pending | Jan 26, 2024 |
| 18423802 | ENHANCING TRANSFER LEARNING FOR LARGE LANGUAGE MODELS | Roku, Inc. | SHAH, SAYED MUNEER | §103 | Non-Final OA | — | Pending | Jan 26, 2024 | |
| 18505398 | TECHNIQUES FOR CONTENT RECOMMENDATION IN MULTIMEDIA ENVIRONMENTS | Roku, Inc. | PRESTON, ASHLEY DAWN | 3689 | §103 | Non-Final OA | 9d | Pending | Nov 09, 2023 |
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