Prosecution Insights
Prosecution Insights
8 pending office actions • 5 art units • 8 examiners • 0 of 8 (0%) have an AI response strategy ready • 14 patents granted in the last 365 days
Based on the USPTO statutory response window for each pending office action. 3 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. 3 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 | 2 (25%) |
| §101 + other | 3 (38%) |
| Double-patenting + other | 1 (12%) |
| Multi-statute (no §101) | 2 (25%) |
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 |
|---|---|---|---|
| OWYANG, MICHELLE N | 1 | 76.1% | +29.4% |
| LITTLE, VANCE M | 1 | 83.8% | +24.6% |
| WYSZYNSKI, AUBREY H | 1 | 89.5% | +12.5% |
| TRAN, HAI | 1 | 62.1% | +31.8% |
| MALINOWSKI, WALTER J | 1 | 69.6% | +52.9% |
| FERRER, JEDIDIAH P | 1 | 52.2% | +40.3% |
| SCHEUNEMANN, RICHARD N | 1 | 6.3% | +8.3% |
| FU, HAO | 1 | 50.1% | +25.1% |
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 |
|---|---|---|---|
| 19068125 | METHODS AND SYSTEMS FOR IP-BASED NETWORK INTRUSION DETECTION AND PREVENTION | LITTLE, VANCE M | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 7 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18939762 | SYSTEMS AND METHODS FOR CONFIGURABLE ORDERED TRANSFORMATION OF DATABASE CONTENT | FERRER, JEDIDIAH P | 45d overdue |
| 18449266 | SEARCH SPACE MINIMIZATION FOR COMPUTERIZED TIME-SERIES DATA FORECASTING SYSTEM | FU, HAO | 32d overdue |
| 18961567 | SYSTEM AND METHOD FOR AUTHENTICATING USERS USING WEAK AUTHENTICATION TECHNIQUES, WITH DIFFERENCES FOR DIFFERENT FEATURES | MALINOWSKI, WALTER J | 15d |
| 19207623 | EVENT-DRIVEN COMPUTER MODELING SYSTEM FOR TIME SERIES DATA | OWYANG, MICHELLE N | — |
| 19066742 | INTRUSION DETECTION AND PREVENTION SYSTEM RULE AUTOMATION AND OPTIMIZATION | WYSZYNSKI, AUBREY H | — |
| 19022409 | SYSTEM AND METHOD FOR TRADING SECURITIES USING PORTFOLIOS DEFINED BY AN ADVISOR | TRAN, HAI | — |
| 18591592 | MACHINE LEARNING MODEL FRAMEWORK TO IDENTIFY POTENTIAL CUSTOMERS AND DISPLAY THEREOF | SCHEUNEMANN, RICHARD N | — |
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 7 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18939762 | SYSTEMS AND METHODS FOR CONFIGURABLE ORDERED TRANSFORMATION OF DATABASE CONTENT | FERRER, JEDIDIAH P | 45d overdue |
| 18449266 | SEARCH SPACE MINIMIZATION FOR COMPUTERIZED TIME-SERIES DATA FORECASTING SYSTEM | FU, HAO | 32d overdue |
| 18961567 | SYSTEM AND METHOD FOR AUTHENTICATING USERS USING WEAK AUTHENTICATION TECHNIQUES, WITH DIFFERENCES FOR DIFFERENT FEATURES | MALINOWSKI, WALTER J | 15d |
| 19207623 | EVENT-DRIVEN COMPUTER MODELING SYSTEM FOR TIME SERIES DATA | OWYANG, MICHELLE N | — |
| 19068125 | METHODS AND SYSTEMS FOR IP-BASED NETWORK INTRUSION DETECTION AND PREVENTION | LITTLE, VANCE M | — |
| 19066742 | INTRUSION DETECTION AND PREVENTION SYSTEM RULE AUTOMATION AND OPTIMIZATION | WYSZYNSKI, AUBREY H | — |
| 19022409 | SYSTEM AND METHOD FOR TRADING SECURITIES USING PORTFOLIOS DEFINED BY AN ADVISOR | TRAN, HAI | — |
| Art Unit | Apps |
|---|---|
| 3695 | 2 |
| 2168 | 1 |
| 2439 | 1 |
| 2153 | 1 |
| 3624 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19207623 | EVENT-DRIVEN COMPUTER MODELING SYSTEM FOR TIME SERIES DATA | OWYANG, MICHELLE N | 2168 | §101§103Other | Non-Final OA | — | Pending | May 14, 2025 |
| 19068125 | METHODS AND SYSTEMS FOR IP-BASED NETWORK INTRUSION DETECTION AND PREVENTION | LITTLE, VANCE M | — | §103DP | Non-Final OA | — | Pending | Mar 03, 2025 |
| 19066742 | INTRUSION DETECTION AND PREVENTION SYSTEM RULE AUTOMATION AND OPTIMIZATION | WYSZYNSKI, AUBREY H | — | §103§112 | Non-Final OA | — | Pending | Feb 28, 2025 |
| 19022409 | SYSTEM AND METHOD FOR TRADING SECURITIES USING PORTFOLIOS DEFINED BY AN ADVISOR | TRAN, HAI | 3695 | §101Other | Final Rejection | — | Pending | Jan 15, 2025 |
| 18961567 | SYSTEM AND METHOD FOR AUTHENTICATING USERS USING WEAK AUTHENTICATION TECHNIQUES, WITH DIFFERENCES FOR DIFFERENT FEATURES | MALINOWSKI, WALTER J | 2439 | §103§112 | Final Rejection | 15d | Pending | Nov 27, 2024 |
| 18939762 | SYSTEMS AND METHODS FOR CONFIGURABLE ORDERED TRANSFORMATION OF DATABASE CONTENT | FERRER, JEDIDIAH P | 2153 | §101§103 | Final Rejection | 45d overdue | Pending | Nov 07, 2024 |
| 18591592 | MACHINE LEARNING MODEL FRAMEWORK TO IDENTIFY POTENTIAL CUSTOMERS AND DISPLAY THEREOF | SCHEUNEMANN, RICHARD N | 3624 | §101§103 | Non-Final OA | — | Pending | Feb 29, 2024 |
| 18449266 | SEARCH SPACE MINIMIZATION FOR COMPUTERIZED TIME-SERIES DATA FORECASTING SYSTEM | FU, HAO | 3695 | §101Other | Final Rejection | 32d overdue | Pending | Aug 14, 2023 |
IP Author helps IP teams respond to office actions faster with AI-generated responses, examiner analytics, and prosecution intelligence.
Start Free Trial