Prosecution Insights
Last updated: August 15, 2026

Softeye Inc.

6 pending office actions • 3 art units • 6 examiners • 0 of 6 (0%) have an AI response strategy ready • 6 patents granted in the last 365 days

Portfolio Summary

6
Total Pending OAs
4
Non-Final OAs
2
Final Rejections
0
Advisory / Quayle

Response Deadline Pressure

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.

3
Overdue
0
Due this week
0
Due this month
0
Due in next 60 days
0
Due later

Deadline Fire Line

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.

-30dToday30d60d90d120d
Overdue (3)

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.

1
Hard (17%)
5
Medium (83%)
0
Easy (0%)
0
Unknown (0%)

Rejection Statute Mix

BucketCases
§101 + other1 (17%)
§103 only4 (67%)
§102 only1 (17%)

Industry Mix

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

0
Life Sciences
0% of docket
2
Information Tech
33% of docket
1
Communications
17% of docket
0
Semiconductors
0% of docket
0
Mechanical / Eng
0% of docket
3
Business / Other
50% 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.

60 h
Manual time on pending OAs
12 h
Time saved (low, 20%)
21 h
Time saved (mid, 35%)
0.5 wks
FTE-weeks freed (mid)

Top Examiners on this docket

ExaminerApps on this docketAllow rateInterview lift
JACOB, AJITH 1 78.9% +4.1%
HICKS, SHIRLEY D. 1 63.1% +55.2%
BAYNES, SAMUEL DAVID 1 85.7% +25.0%
YANG, JIANXUN 1 74.7% +18.6%
AKHAVANNIK, HADI 1 85.9% +13.0%
MAHROUKA, WASSIM 1 86.0% +7.8%

Quick Wins (3)

Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 3 ordered by deadline are shown.

App #TitleExaminerDue in
18185366 APPARATUS AND METHODS FOR AUGMENTING VISION WITH REGION-OF-INTEREST BASED PROCESSING MAHROUKA, WASSIM 85d overdue
18983169 MACHINE-LEARNING ALGORITHMS FOR LOW-POWER APPLICATIONS BAYNES, SAMUEL DAVID
18983242 MACHINE-LEARNING ALGORITHMS FOR LOW-POWER APPLICATIONS AKHAVANNIK, HADI

Hard Cases (1)

Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 1 ordered by deadline are shown.

App #TitleExaminerDue in
19081936 FOUNDATION MODEL PIPELINE FOR REAL-TIME EMBEDDED DEVICES JACOB, AJITH 93d overdue

Interview Candidates (4)

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 4 ordered by deadline are shown.

App #TitleExaminerDue in
19081951 FOUNDATION MODEL PIPELINE FOR REAL-TIME EMBEDDED DEVICES HICKS, SHIRLEY D. 98d overdue
18983169 MACHINE-LEARNING ALGORITHMS FOR LOW-POWER APPLICATIONS BAYNES, SAMUEL DAVID
18983261 MACHINE-LEARNING ALGORITHMS FOR LOW-POWER APPLICATIONS YANG, JIANXUN
18983242 MACHINE-LEARNING ALGORITHMS FOR LOW-POWER APPLICATIONS AKHAVANNIK, HADI

Top Art Units

Art UnitApps
2161 1
2168 1
2665 1

Pending Office Actions

App #TitleExaminerArt UnitStatutesStatusDue inAIFiled
19081936 FOUNDATION MODEL PIPELINE FOR REAL-TIME EMBEDDED DEVICES JACOB, AJITH 2161 §101§103 Non-Final OA 93d overdue Pending Mar 17, 2025
19081951 FOUNDATION MODEL PIPELINE FOR REAL-TIME EMBEDDED DEVICES HICKS, SHIRLEY D. 2168 §102 Final Rejection 98d overdue Pending Mar 17, 2025
18983169 MACHINE-LEARNING ALGORITHMS FOR LOW-POWER APPLICATIONS BAYNES, SAMUEL DAVID §103 Non-Final OA Pending Dec 16, 2024
18983261 MACHINE-LEARNING ALGORITHMS FOR LOW-POWER APPLICATIONS YANG, JIANXUN §103 Non-Final OA Pending Dec 16, 2024
18983242 MACHINE-LEARNING ALGORITHMS FOR LOW-POWER APPLICATIONS AKHAVANNIK, HADI §103 Non-Final OA Pending Dec 16, 2024
18185366 APPARATUS AND METHODS FOR AUGMENTING VISION WITH REGION-OF-INTEREST BASED PROCESSING MAHROUKA, WASSIM 2665 §103 Final Rejection 85d overdue Pending Mar 16, 2023

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