Prosecution Insights
Prosecution Insights
6 pending office actions • 6 art units • 6 examiners • 0 of 6 (0%) have an AI response strategy ready • 16 patents granted in the last 365 days
Based on the USPTO statutory response window for each pending office action. 6 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 6 of the docket's apps have a known mailing date.
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 |
|---|---|
| §101 only | 1 (17%) |
| §103 only | 3 (50%) |
| §102 only | 2 (33%) |
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 |
|---|---|---|---|
| ORTIZ DITREN, BELIX M | 1 | 84.0% | +2.0% |
| CHEN, BIAO | 1 | 84.4% | +26.3% |
| PATEL, DIPEN M | 1 | 20.5% | +24.8% |
| SULTANA, NADIRA | 1 | 74.3% | +30.4% |
| MCINTOSH, ANDREW T | 1 | 77.1% | +18.0% |
| LEE, WILLIAM MICHAEL | 1 | — | — |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18764005 | COLLAGE GENERATION OF COMPLEMENTARY OBJECTS | CHEN, BIAO | 15d overdue |
| 19048322 | DYNAMIC FILTER RECOMMENDATIONS | ORTIZ DITREN, BELIX M | 84d |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18626137 | RECOMMENDATION CAMPAIGNS BASED ON PREDICTED SHORT-TERM USER BEHAVIOR AND PREDICTED LONG-TERM USER BEHAVIOR | PATEL, DIPEN M | 9d overdue |
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 |
|---|---|---|---|
| 18764005 | COLLAGE GENERATION OF COMPLEMENTARY OBJECTS | CHEN, BIAO | 15d overdue |
| 18626137 | RECOMMENDATION CAMPAIGNS BASED ON PREDICTED SHORT-TERM USER BEHAVIOR AND PREDICTED LONG-TERM USER BEHAVIOR | PATEL, DIPEN M | 9d overdue |
| 18335212 | DEBIASED TRAINING OF MACHINE LEARNING SYSTEMS | MCINTOSH, ANDREW T | 3d overdue |
| 18499984 | IDENTIFYING IMAGE BASED CONTENT ITEMS USING A LARGE LANGUAGE MODEL | SULTANA, NADIRA | 83d |
| Art Unit | Apps |
|---|---|
| 2164 | 1 |
| 2611 | 1 |
| 3621 | 1 |
| 2653 | 1 |
| 2144 | 1 |
| 2145 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19048322 | DYNAMIC FILTER RECOMMENDATIONS | ORTIZ DITREN, BELIX M | 2164 | §102 | Final Rejection | 84d | Pending | Feb 07, 2025 |
| 18764005 | COLLAGE GENERATION OF COMPLEMENTARY OBJECTS | CHEN, BIAO | 2611 | §103 | Non-Final OA | 15d overdue | Pending | Jul 03, 2024 |
| 18626137 | RECOMMENDATION CAMPAIGNS BASED ON PREDICTED SHORT-TERM USER BEHAVIOR AND PREDICTED LONG-TERM USER BEHAVIOR | PATEL, DIPEN M | 3621 | §101 | Non-Final OA | 9d overdue | Pending | Apr 03, 2024 |
| 18499984 | IDENTIFYING IMAGE BASED CONTENT ITEMS USING A LARGE LANGUAGE MODEL | SULTANA, NADIRA | 2653 | §102 | Final Rejection | 83d | Pending | Nov 01, 2023 |
| 18335212 | DEBIASED TRAINING OF MACHINE LEARNING SYSTEMS | MCINTOSH, ANDREW T | 2144 | §103 | Non-Final OA | 3d overdue | Pending | Jun 15, 2023 |
| 18166415 | SEQUENTIAL MODEL FOR DETERMINING USER REPRESENTATIONS | LEE, WILLIAM MICHAEL | 2145 | §103 | Non-Final OA | 31d overdue | Pending | Feb 08, 2023 |
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