Prosecution Insights
Prosecution Insights
Technology areas: Computing & Software • Networking & Security • Communications
7 pending office actions • 5 art units • 7 examiners • 0 of 7 (0%) have an AI response strategy ready • 13 patents granted in the last 365 days
Varonis Systems Inc. has 6 pending office actions currently active in the Networking & Security technology area. These actions are distributed among 6 distinct examiners, meaning each examiner is responsible for 1 pending matter. This 1 to 1 ratio between actions and examiners shows a lack of examiner-specific concentration in the current workload. Consequently, the company must manage 6 separate prosecution tracks without the benefit of examiner-level familiarity across cases.
The portfolio's activity spans 5 distinct art units, showing a technical footprint across multiple areas. AMEVIGBE, KOMI NOUNYANOU is the busiest examiner with 1 pending office action, matching the count of every other examiner involved. For the legal team, this distribution across 5 distinct art units requires managing multiple simultaneous examiner relationships rather than focusing on 1 point of contact. This variety in art units indicates that the networking and security innovations cover 5 different sub-specialties.
With 6 pending office actions and 6 distinct examiners, the prosecution environment is decentralized. The presence of 5 distinct art units involves multiple supervisory chains within the patent office. Because AMEVIGBE, KOMI NOUNYANOU only handles 1 pending office action, there is no examiner whose decisions disproportionately affect the overall portfolio of 6 actions. This structure necessitates a case-by-case approach to prosecution rather than a unified examiner-specific strategy.
Based on the USPTO statutory response window for each pending office action. 2 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 | 1 (14%) |
| §101 + other | 2 (29%) |
| §103 only | 2 (29%) |
| §112 only | 1 (14%) |
| Double-patenting only | 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 |
|---|---|---|---|
| DO, KHANG D | 1 | 80.8% | +43.7% |
| AMEVIGBE, KOMI NOUNYANOU | 1 | 0.0% | +0.0% |
| NEWAY, SAMUEL G | 1 | 75.1% | +7.2% |
| YI, HYUNGJUN B | 1 | 32.1% | +25.8% |
| WONG, HUEN | 1 | 60.1% | +46.1% |
| CHOUDHURY, RAQIUL A | 1 | 86.5% | +5.7% |
| NANO, SARGON N | 1 | 80.8% | -1.4% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19051350 | INTEGRATED SECURITY FOR CLOUD APPLICATIONS | DO, KHANG D | — |
| 18537595 | Service Security Control | CHOUDHURY, RAQIUL A | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 4 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18383076 | Email Security and Prevention of Phishing Attacks Using a Large Language Model (LLM) Engine | NANO, SARGON N | 30d overdue |
| 18788970 | Combined Machine Learning and Large Language Models | NEWAY, SAMUEL G | 5d overdue |
| 18945613 | Automatic Detection and Handling of Security-Related Anomalies by Utilizing Machine Learning and a Large Language Model | AMEVIGBE, KOMI NOUNYANOU | — |
| 18622949 | Automated AI-Based Handling of Requests for Privileges Escalation | YI, HYUNGJUN B | — |
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 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19051350 | INTEGRATED SECURITY FOR CLOUD APPLICATIONS | DO, KHANG D | — |
| 18622949 | Automated AI-Based Handling of Requests for Privileges Escalation | YI, HYUNGJUN B | — |
| 18435542 | Object Permissions Management | WONG, HUEN | — |
| Art Unit | Apps |
|---|---|
| 2493 | 1 |
| 2657 | 1 |
| 2168 | 1 |
| 2444 | 1 |
| 2443 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19051350 | INTEGRATED SECURITY FOR CLOUD APPLICATIONS | DO, KHANG D | — | DP | Non-Final OA | — | Pending | Feb 12, 2025 |
| 18945613 | Automatic Detection and Handling of Security-Related Anomalies by Utilizing Machine Learning and a Large Language Model | AMEVIGBE, KOMI NOUNYANOU | 2493 | §103 | Final Rejection | — | Pending | Nov 13, 2024 |
| 18788970 | Combined Machine Learning and Large Language Models | NEWAY, SAMUEL G | 2657 | §101§103§112 | Non-Final OA | 5d overdue | Pending | Jul 30, 2024 |
| 18622949 | Automated AI-Based Handling of Requests for Privileges Escalation | YI, HYUNGJUN B | — | §101§103 | Non-Final OA | — | Pending | Mar 31, 2024 |
| 18435542 | Object Permissions Management | WONG, HUEN | 2168 | §103 | Final Rejection | — | Pending | Feb 07, 2024 |
| 18537595 | Service Security Control | CHOUDHURY, RAQIUL A | 2444 | §112 | Final Rejection | — | Pending | Dec 12, 2023 |
| 18383076 | Email Security and Prevention of Phishing Attacks Using a Large Language Model (LLM) Engine | NANO, SARGON N | 2443 | §101 | Final Rejection | 30d overdue | Pending | Oct 24, 2023 |
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