Prosecution Insights
Prosecution Insights
3 pending office actions • 2 art units • 3 examiners • 0 of 3 (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. 1 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 |
|---|---|
| §101 only | 1 (33%) |
| §101 + other | 2 (67%) |
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 |
|---|---|---|---|
| RACIC, MILENA | 1 | 48.0% | +44.5% |
| SERROU, ABDELALI | 1 | 74.4% | +30.1% |
| PRESTON, JOHN O | 1 | 28.3% | +7.2% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18058665 | COMPUTING SYSTEM FOR USE IN OUTPUTTING CANDIDATE TAX CATEGORIES FOR AN ARTICLE | PRESTON, JOHN O | 15d |
| 19076995 | ARTIFICIAL INTELLIGENCE MODEL FOR TAXABILITY CATEGORY MAPPING | RACIC, MILENA | — |
| 18482666 | GENERATION OF VERBOSE TAX CATEGORY DESCRIPTIONS USING A GENERATIVE LANGUAGE MODEL | SERROU, ABDELALI | — |
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 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19076995 | ARTIFICIAL INTELLIGENCE MODEL FOR TAXABILITY CATEGORY MAPPING | RACIC, MILENA | — |
| 18482666 | GENERATION OF VERBOSE TAX CATEGORY DESCRIPTIONS USING A GENERATIVE LANGUAGE MODEL | SERROU, ABDELALI | — |
| Art Unit | Apps |
|---|---|
| 2659 | 1 |
| 3693 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19076995 | ARTIFICIAL INTELLIGENCE MODEL FOR TAXABILITY CATEGORY MAPPING | RACIC, MILENA | — | §101§103Other | Non-Final OA | — | Pending | Mar 11, 2025 |
| 18482666 | GENERATION OF VERBOSE TAX CATEGORY DESCRIPTIONS USING A GENERATIVE LANGUAGE MODEL | SERROU, ABDELALI | 2659 | §101§103 | Final Rejection | — | Pending | Oct 06, 2023 |
| 18058665 | COMPUTING SYSTEM FOR USE IN OUTPUTTING CANDIDATE TAX CATEGORIES FOR AN ARTICLE | PRESTON, JOHN O | 3693 | §101 | Final Rejection | 15d | Pending | Nov 23, 2022 |
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