Prosecution Insights
Prosecution Insights
Technology areas: Computing & Software • Transportation, E-Commerce & Mechanical Systems
7 pending office actions • 5 art units • 7 examiners • 0 of 7 (0%) have an AI response strategy ready • 20 patents granted in the last 365 days
BOLD Limited operates within the Computing & Software technology area. The company currently faces 6 pending office actions. These matters are spread across 5 distinct art units, indicating that the company's software innovations are subject to review by several different specialized groups. This variety in art units suggests that the portfolio covers a range of technical applications within the computing field.
The prosecution involves 6 distinct examiners, which means each of the 6 pending office actions is being handled by a different individual. GOMEZ, CHRISTOPHER ALBERT is identified as the busiest examiner for this applicant. This examiner is responsible for 1 pending office action. Because the busiest examiner handles only 1 action, the company's prosecution efforts are not concentrated under any single official's discretion.
With 5 distinct art units and 6 distinct examiners, the portfolio is subject to a broad range of examination styles. GOMEZ, CHRISTOPHER ALBERT's 1 pending office action represents a small fraction of the total workload. Practitioners should prepare for diverse feedback across the 5 distinct art units assigned to these cases.
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 | 1 (14%) |
| §101 + other | 4 (57%) |
| §103 only | 1 (14%) |
| Double-patenting + other | 1 (14%) |
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 |
|---|---|---|---|
| GOMEZ, CHRISTOPHER ALBERT | 1 | 26.4% | +30.9% |
| PATEL, DIPEN M | 1 | 20.1% | +23.8% |
| RYLANDER, BART I | 1 | 68.9% | +10.1% |
| ANDERSON, SCOTT C | 1 | 58.6% | +31.6% |
| WILLIS, AMANDA LYNN | 1 | 35.8% | +26.3% |
| ROSTAMI, MOHAMMAD S | 1 | 67.0% | +25.9% |
| DAUD, ABDULLAH AHMED | 1 | 55.4% | +31.1% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 5 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18205431 | PARALLEL INTERACTION INTERFACE FOR MACHINE LEARNING MODELS | ROSTAMI, MOHAMMAD S | 9d overdue |
| 19038282 | PROFILE-BASED DATA AGGREGATION FOR DYNAMIC DOCUMENT GENERATION | GOMEZ, CHRISTOPHER ALBERT | — |
| 19009851 | MACHINE LEARNING-BASED METHOD AND SYSTEM TO RETAIN CUSTOMERS | PATEL, DIPEN M | — |
| 18622747 | DYNAMIC CONTENT GENERATOR | RYLANDER, BART I | — |
| 18434675 | MACHINE LEARNING DOCUMENT PARSER | ANDERSON, SCOTT C | — |
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 |
|---|---|---|---|
| 18510581 | SYSTEMS AND METHODS FOR CREATING ENHANCED DOCUMENTS FOR PERFECT AUTOMATED PARSING | WILLIS, AMANDA LYNN | 44d overdue |
| 18205431 | PARALLEL INTERACTION INTERFACE FOR MACHINE LEARNING MODELS | ROSTAMI, MOHAMMAD S | 9d overdue |
| 18160166 | SYSTEMS AND METHODS FOR IMPROVED SEARCH AND INTERACTION WITH AN ONLINE PROFILE | DAUD, ABDULLAH AHMED | 29d |
| 19038282 | PROFILE-BASED DATA AGGREGATION FOR DYNAMIC DOCUMENT GENERATION | GOMEZ, CHRISTOPHER ALBERT | — |
| 19009851 | MACHINE LEARNING-BASED METHOD AND SYSTEM TO RETAIN CUSTOMERS | PATEL, DIPEN M | — |
| 18622747 | DYNAMIC CONTENT GENERATOR | RYLANDER, BART I | — |
| 18434675 | MACHINE LEARNING DOCUMENT PARSER | ANDERSON, SCOTT C | — |
| Art Unit | Apps |
|---|---|
| 3628 | 1 |
| 3621 | 1 |
| 2156 | 1 |
| 2154 | 1 |
| 2164 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19038282 | PROFILE-BASED DATA AGGREGATION FOR DYNAMIC DOCUMENT GENERATION | GOMEZ, CHRISTOPHER ALBERT | 3628 | §101 | Non-Final OA | — | Pending | Jan 27, 2025 |
| 19009851 | MACHINE LEARNING-BASED METHOD AND SYSTEM TO RETAIN CUSTOMERS | PATEL, DIPEN M | 3621 | §101§103 | Final Rejection | — | Pending | Jan 03, 2025 |
| 18622747 | DYNAMIC CONTENT GENERATOR | RYLANDER, BART I | — | §101§103 | Non-Final OA | — | Pending | Mar 29, 2024 |
| 18434675 | MACHINE LEARNING DOCUMENT PARSER | ANDERSON, SCOTT C | — | §101§103§112 | Non-Final OA | — | Pending | Feb 06, 2024 |
| 18510581 | SYSTEMS AND METHODS FOR CREATING ENHANCED DOCUMENTS FOR PERFECT AUTOMATED PARSING | WILLIS, AMANDA LYNN | 2156 | §103DP | Non-Final OA | 44d overdue | Pending | Nov 15, 2023 |
| 18205431 | PARALLEL INTERACTION INTERFACE FOR MACHINE LEARNING MODELS | ROSTAMI, MOHAMMAD S | 2154 | §101§103 | Final Rejection | 9d overdue | Pending | Jun 02, 2023 |
| 18160166 | SYSTEMS AND METHODS FOR IMPROVED SEARCH AND INTERACTION WITH AN ONLINE PROFILE | DAUD, ABDULLAH AHMED | 2164 | §103 | Final Rejection | 29d | Pending | Jan 26, 2023 |
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