Prosecution Insights
Last updated: October 04, 2026

BMC Software, Inc.

Technology areas: Computing & Software • Networking & Security • Communications

4 pending office actions • 4 art units • 4 examiners • 0 of 4 (0%) have an AI response strategy ready • 3 patents granted in the last 365 days

Analysis

BMC Software, Inc. currently manages 4 pending office actions within the Computing & Software technology area. These matters are distributed across distinct examiners, with 4 such individuals identified in the data. The actions are also spread across 4 distinct art units. This ratio between pending actions and examiners suggests that each application in the portfolio is navigating a unique examination path. Practitioners should prepare for diverse perspectives rather than a consolidated strategy across these filings.

The busiest examiner identified in the portfolio is CHU, GABRIEL L, who is responsible for 1 pending office action. While this examiner holds the highest volume of pending work for the company, the count of 1 indicates that no single examiner currently dominates the active prosecution pipeline. The presence of the distinct art units further confirms that the pending office actions are likely addressing varied technical sub-sectors within the broader Computing & Software field. Legal teams should tailor their arguments to the specific tendencies of each examiner and unit involved.

Written from this page's own data; every figure is computed from USPTO records and verified before publication.

Portfolio Summary

4
Total Pending OAs
2
Non-Final OAs
2
Final Rejections
0
Advisory / Quayle

Response Deadline Pressure

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.

1
Overdue
0
Due this week
0
Due this month
0
Due in next 60 days
0
Due later

Case Difficulty Mix

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.

2
Hard (50%)
2
Medium (50%)
0
Easy (0%)
0
Unknown (0%)

Rejection Statute Mix

BucketCases
§101 only2 (50%)
§103 only2 (50%)

Industry Mix

How the docket's pending cases split across USPTO tech-center bands.

0
Life Sciences
0% of docket
3
Information Tech
75% of docket
1
Communications
25% of docket
0
Semiconductors
0% of docket
0
Mechanical / Eng
0% of docket
0
Business / Other
0% of docket

Time-on-OA Estimate

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.

40 h
Manual time on pending OAs
8 h
Time saved (low, 20%)
14 h
Time saved (mid, 35%)
0.3 wks
FTE-weeks freed (mid)

Top Examiners on this docket

ExaminerApps on this docketAllow rateInterview lift
CHU, GABRIEL L 1 78.8% -2.2%
ORTIZ SANCHEZ, MICHAEL 1 67.1% +27.2%
WILSON, YOLANDA L 1 83.7% +5.8%
BENGZON, GREG C 1 57.9% +7.0%

Hard Cases (2)

Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 2 ordered by deadline are shown.

App #TitleExaminerDue in
19269505 SELF-OPTIMIZING CONTEXT-AWARE PROBLEM IDENTIFICATION FROM INFORMATION TECHNOLOGY INCIDENT REPORTS CHU, GABRIEL L —
18332336 APPLICATION STATE PREDICTION USING COMPONENT STATE WILSON, YOLANDA L —

Interview Candidates (1)

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 1 ordered by deadline are shown.

App #TitleExaminerDue in
18622841 PROMPT ORCHESTRATION FOR VIRTUAL AGENTS WITH DIGRESSION CAPABILITIES ORTIZ SANCHEZ, MICHAEL —

Top Art Units

Art UnitApps
2114 1
2656 1
2113 1
2444 1

Pending Office Actions

App #TitleExaminerArt UnitStatutesStatusDue inAIFiled
19269505 SELF-OPTIMIZING CONTEXT-AWARE PROBLEM IDENTIFICATION FROM INFORMATION TECHNOLOGY INCIDENT REPORTS CHU, GABRIEL L 2114 §101Other Non-Final OA — Pending Jul 15, 2025
18622841 PROMPT ORCHESTRATION FOR VIRTUAL AGENTS WITH DIGRESSION CAPABILITIES ORTIZ SANCHEZ, MICHAEL 2656 §103 Non-Final OA — Pending Mar 29, 2024
18332336 APPLICATION STATE PREDICTION USING COMPONENT STATE WILSON, YOLANDA L 2113 §101 Final Rejection — Pending Jun 09, 2023
18194612 SMART PATCH RISK PREDICTION AND VALIDATION FOR LARGE SCALE DISTRIBUTED INFRASTRUCTURE BENGZON, GREG C 2444 §103 Final Rejection 4d overdue Pending Mar 31, 2023

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