Prosecution Insights
Prosecution Insights
Technology area: Transportation, E-Commerce & Mechanical Systems
6 pending office actions • 6 art units • 6 examiners • 0 of 6 (0%) have an AI response strategy ready • 10 patents granted in the last 365 days
Yext Inc. is currently managing 6 pending office actions within the Transportation, E-Commerce & Mechanical Systems technology area. These actions are widely distributed across 6 distinct examiners and 6 distinct art units. This ratio between actions, examiners, and art units indicates that every pending matter is being evaluated by a different person in a different specialized group. Such a distribution suggests that the company's 6 pending applications cover a broad range of technical sub-specialties.
JARRETT, SCOTT L is the busiest examiner for the portfolio, with 1 pending office action. Because there are 6 distinct examiners for 6 pending office actions, the workload is spread such that no single examiner has more influence than another over the pending portfolio. The involvement of 6 distinct art units requires the company to navigate a diverse range of examination environments and technical standards simultaneously. This lack of concentration means that the outcome of a single office action is unlikely to directly influence the others based on examiner consistency.
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 | 2 (33%) |
| §101 + other | 3 (50%) |
| §103 only | 1 (17%) |
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 |
|---|---|---|---|
| JARRETT, SCOTT L | 1 | 52.0% | +47.3% |
| LAU, KAITLYN RENEE | 1 | 60.0% | +66.7% |
| SEIBERT, CHRISTOPHER B | 1 | 57.4% | +42.9% |
| SENSENIG, SHAUN D | 1 | 14.2% | +16.3% |
| MEIS, JON CHRISTOPHER | 1 | 33.3% | +52.4% |
| O'SHEA, BRENDAN S | 1 | 30.7% | +38.1% |
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 |
|---|---|---|---|
| 18933107 | ONLINE MERCHANT REVIEW SYSTEM AND METHOD UTILIZING DYNAMIC URL REDIRECTION FOR DISTRIBUTING REVIEW REQUESTS | JARRETT, SCOTT L | — |
| 18177066 | COMPUTED VALUES FOR KNOWLEDGE GRAPH | LAU, KAITLYN RENEE | — |
| 18104618 | SEARCH RESULT GENERATION USING NAMED ENTITY RECOGNITION | SEIBERT, CHRISTOPHER B | — |
| 17876295 | MERCHANT LISTING VERIFICATION SYSTEM | SENSENIG, SHAUN D | — |
| 16535690 | BUSINESS LISTING UPDATE MANAGEMENT | O'SHEA, BRENDAN S | — |
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 6 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17815786 | SYSTEM AND METHOD FOR ARTIFICIAL INTELLIGENCE CLEANING TRANSFORM | MEIS, JON CHRISTOPHER | 34d |
| 18933107 | ONLINE MERCHANT REVIEW SYSTEM AND METHOD UTILIZING DYNAMIC URL REDIRECTION FOR DISTRIBUTING REVIEW REQUESTS | JARRETT, SCOTT L | — |
| 18177066 | COMPUTED VALUES FOR KNOWLEDGE GRAPH | LAU, KAITLYN RENEE | — |
| 18104618 | SEARCH RESULT GENERATION USING NAMED ENTITY RECOGNITION | SEIBERT, CHRISTOPHER B | — |
| 17876295 | MERCHANT LISTING VERIFICATION SYSTEM | SENSENIG, SHAUN D | — |
| 16535690 | BUSINESS LISTING UPDATE MANAGEMENT | O'SHEA, BRENDAN S | — |
| Art Unit | Apps |
|---|---|
| 3625 | 1 |
| 2148 | 1 |
| 3688 | 1 |
| 3629 | 1 |
| 2654 | 1 |
| 3600 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18933107 | ONLINE MERCHANT REVIEW SYSTEM AND METHOD UTILIZING DYNAMIC URL REDIRECTION FOR DISTRIBUTING REVIEW REQUESTS | JARRETT, SCOTT L | 3625 | §101 | Final Rejection | — | Pending | Oct 31, 2024 |
| 18177066 | COMPUTED VALUES FOR KNOWLEDGE GRAPH | LAU, KAITLYN RENEE | 2148 | §101§103§112 | Non-Final OA | — | Pending | Mar 01, 2023 |
| 18104618 | SEARCH RESULT GENERATION USING NAMED ENTITY RECOGNITION | SEIBERT, CHRISTOPHER B | 3688 | §101§103 | Non-Final OA | — | Pending | Feb 01, 2023 |
| 17876295 | MERCHANT LISTING VERIFICATION SYSTEM | SENSENIG, SHAUN D | 3629 | §101 | Final Rejection | — | Pending | Jul 28, 2022 |
| 17815786 | SYSTEM AND METHOD FOR ARTIFICIAL INTELLIGENCE CLEANING TRANSFORM | MEIS, JON CHRISTOPHER | 2654 | §103 | Final Rejection | 34d | Pending | Jul 28, 2022 |
| 16535690 | BUSINESS LISTING UPDATE MANAGEMENT | O'SHEA, BRENDAN S | 3600 | §101§103 | Non-Final OA | — | Pending | Aug 08, 2019 |
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