Prosecution Insights
Prosecution Insights
3 pending office actions • 1 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready • 4 patents granted in the last 365 days
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 + other | 1 (33%) |
| §103 only | 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 |
|---|---|---|---|
| OLAEGBE, MUDASIRU K | 1 | 73.6% | +14.6% |
| KIM, DAVID | 1 | 100.0% | +0.0% |
| HAJIABBASI, AMIR MAHDI | 1 | 86.2% | +7.1% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18534054 | SYSTEM AND METHOD FOR DETERMINING CYBERSECURITY RISK LEVEL OF ELECTRONIC MESSAGES | HAJIABBASI, AMIR MAHDI | — |
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 |
|---|---|---|---|
| 18425932 | SYSTEM AND METHOD FOR INCREASING EFFICIENCY IN MODEL CORRECTION IN SUPERVISED SYSTEMS | KIM, DAVID | — |
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 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19196556 | SYSTEM AND METHOD FOR GENERATING FRAUD REPORT USING LARGE LANGUAGE MODEL | OLAEGBE, MUDASIRU K | — |
| Art Unit | Apps |
|---|---|
| 2407 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19196556 | SYSTEM AND METHOD FOR GENERATING FRAUD REPORT USING LARGE LANGUAGE MODEL | OLAEGBE, MUDASIRU K | — | §103 | Non-Final OA | — | Pending | May 01, 2025 |
| 18425932 | SYSTEM AND METHOD FOR INCREASING EFFICIENCY IN MODEL CORRECTION IN SUPERVISED SYSTEMS | KIM, DAVID | — | §101§103 | Non-Final OA | — | Pending | Jan 29, 2024 |
| 18534054 | SYSTEM AND METHOD FOR DETERMINING CYBERSECURITY RISK LEVEL OF ELECTRONIC MESSAGES | HAJIABBASI, AMIR MAHDI | 2407 | §103 | Non-Final OA | — | Pending | Dec 08, 2023 |
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