Prosecution Insights
Prosecution Insights
2 pending office actions • 0 art units • 2 examiners • 0 of 2 (0%) have an AI response strategy ready
Epiq Ediscovery Solutions Inc. is managing 2 pending office actions. These matters are assigned to 2 distinct examiners. SERROU, ABDELALI is the busiest examiner for the portfolio, responsible for 1 pending office action. With 2 distinct examiners involved, the company must manage 2 separate prosecution tracks for its 2 pending office actions. This distribution suggests that the company's current prosecution is not concentrated under a single examiner.
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 (50%) |
| §102 only | 1 (50%) |
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 |
|---|---|---|---|
| SERROU, ABDELALI | 1 | 74.2% | +29.8% |
| ZHANG, DUAN | 1 | 60.8% | +18.6% |
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 |
|---|---|---|---|
| 19005802 | METHOD FOR RECOMMENDING AND IMPLEMENTING COMMUNICATION OPTIMIZATIONS | 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 |
|---|---|---|---|
| 19005802 | METHOD FOR RECOMMENDING AND IMPLEMENTING COMMUNICATION OPTIMIZATIONS | SERROU, ABDELALI | — |
| 18667896 | SYSTEM AND METHOD FOR TEACHING MACHINE LEARNING MODELS TO RECOGNIZE CONCEPTS IN MULTIMEDIA DOCUMENTS THROUGH NATURAL LANGUAGE INTERACTION AND MIXED-INITIATIVE LEARNING | ZHANG, DUAN | — |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19005802 | METHOD FOR RECOMMENDING AND IMPLEMENTING COMMUNICATION OPTIMIZATIONS | SERROU, ABDELALI | — | §101§102§103 | Non-Final OA | — | Pending | Dec 30, 2024 |
| 18667896 | SYSTEM AND METHOD FOR TEACHING MACHINE LEARNING MODELS TO RECOGNIZE CONCEPTS IN MULTIMEDIA DOCUMENTS THROUGH NATURAL LANGUAGE INTERACTION AND MIXED-INITIATIVE LEARNING | ZHANG, DUAN | — | §102 | Non-Final OA | — | Pending | May 17, 2024 |
IP Author helps IP teams respond to office actions faster with AI-generated responses, examiner analytics, and prosecution intelligence.
Start Free Trial