Technology areas: Computing & Software • Communications
12 pending office actions • 2 clients • 12 examiners • 10 art units • 0 of 12 (0%) have an AI response strategy ready • 48 patents granted in the last 365 days
This Intuit profile covers Computing & Software and reports 12 pending office actions. The associated career record contains 34995 applications, a resolved allowance rate of 85.36%, and an average of 3.05 office actions per allowance.
Those historical figures describe the broader record associated with the profile, not necessarily the outcome of the open Intuit matters. The allowance rate indicates that a majority of resolved applications reached allowance, while the action average shows that allowance commonly followed multiple examination exchanges.
For a practitioner, the open software docket calls for coordinated review of claim scope, technical terminology, and response timing. The larger career record supports standardized portfolio metrics, but individual Intuit matters should still be evaluated for their own examiner issues and prosecution objectives.
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 (17%) |
| §101 + other | 4 (33%) |
| §103 only | 4 (33%) |
| Multi-statute (no §101) | 2 (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 |
|---|---|---|---|
| BOGGS JR., JAMES | 1 | 62.9% | +36.0% |
| SERRAGUARD, SEAN ERIN | 1 | 69.3% | +34.3% |
| MORRISON, JAY A | 1 | 81.1% | +23.3% |
| DAYE, CHELCIE L | 1 | 76.6% | +16.0% |
| CHEN, KUANG FU | 1 | 79.8% | +69.0% |
| ZATEZALO, MISHA DAYLA | 1 | — | — |
| LE, MICHAEL HOANG | 1 | — | — |
| VINCENT, DAVID ROBERT | 1 | 80.4% | +3.8% |
| TENGBUMROONG, NATHAN NARA | 1 | 40.7% | +34.1% |
| ANNIS, PETER THOMAS | 1 | — | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18930938 | SYNTHETIC KNOWLEDGE INGESTION FOR ENHANCING LARGE LANGUAGE MODEL PERFORMANCE | SERRAGUARD, SEAN ERIN | — |
| 18791185 | ADAPTIVE INFORMATION RETRIEVAL UTILIZING SEMANTIC AND LEXICAL SCORING | MORRISON, JAY A | — |
| 18744366 | TRAINING DATA GENERATION FOR LARGE LANGUAGE MODEL FINE-TUNING AND/OR BENCHMARKING | CHEN, KUANG FU | — |
| 18651543 | STREAMING DATA SET GENERATION FOR FINE-TUNING MODELS | ZATEZALO, MISHA DAYLA | — |
| 18592377 | ASSISTIVE GENERATIVE AI-BASED RESPONSES | VINCENT, DAVID ROBERT | — |
| 18497884 | AUTOMIZED GENERATION OF INSIGHTFUL AND CONFIDENT DATA INSIGHTS | ANNIS, PETER THOMAS | — |
| 18495172 | WORKFLOW ASSISTANT WITH GENERATIVE ARTIFICIAL INTELLIGENCE | PENG, STEVEN | — |
| 18372660 | EXPERT FEEDBACK LOOP FOR RESOLVING AMBIGUITY | ROY, SANCHITA | — |
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 |
|---|---|---|---|
| 18424572 | SLANG USAGE DETECTION AND MITIGATION FOR LARGE LANGUAGE MODELS | TENGBUMROONG, NATHAN NARA | 49d overdue |
| 19096438 | LANGUAGE MODEL ADAPTATION FOR DOMAIN-FOCUSED TEXT GENERATION | BOGGS JR., JAMES | — |
| 18930938 | SYNTHETIC KNOWLEDGE INGESTION FOR ENHANCING LARGE LANGUAGE MODEL PERFORMANCE | SERRAGUARD, SEAN ERIN | — |
| 18791185 | ADAPTIVE INFORMATION RETRIEVAL UTILIZING SEMANTIC AND LEXICAL SCORING | MORRISON, JAY A | — |
| 18782876 | CONTEXT-AWARE INFORMATION RETRIEVAL | DAYE, CHELCIE L | — |
| 18744366 | TRAINING DATA GENERATION FOR LARGE LANGUAGE MODEL FINE-TUNING AND/OR BENCHMARKING | CHEN, KUANG FU | — |
| Client (Assignee) | Pending OAs |
|---|---|
| INTUIT INC. | 8 |
| Intuit | 4 |
| Art Unit | Apps |
|---|---|
| 2657 | 2 |
| 2151 | 1 |
| 2161 | 1 |
| 2143 | 1 |
| 2141 | 1 |
| 2123 | 1 |
| 2654 | 1 |
| 4100 | 1 |
| 2125 | 1 |
| 2146 | 1 |
| App # | Title | Client | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|---|
| 19096438 | LANGUAGE MODEL ADAPTATION FOR DOMAIN-FOCUSED TEXT GENERATION | Intuit Inc. | BOGGS JR., JAMES | 2657 | §103 | Non-Final OA | — | Pending | Mar 31, 2025 |
| 18930938 | SYNTHETIC KNOWLEDGE INGESTION FOR ENHANCING LARGE LANGUAGE MODEL PERFORMANCE | Intuit Inc. | SERRAGUARD, SEAN ERIN | 2657 | §102§103 | Non-Final OA | — | Pending | Oct 29, 2024 |
| 18791185 | ADAPTIVE INFORMATION RETRIEVAL UTILIZING SEMANTIC AND LEXICAL SCORING | Intuit Inc. | MORRISON, JAY A | 2151 | §101 | Final Rejection | — | Pending | Jul 31, 2024 |
| 18782876 | CONTEXT-AWARE INFORMATION RETRIEVAL | Intuit, Inc. | DAYE, CHELCIE L | 2161 | §103 | Final Rejection | — | Pending | Jul 24, 2024 |
| 18744366 | TRAINING DATA GENERATION FOR LARGE LANGUAGE MODEL FINE-TUNING AND/OR BENCHMARKING | Intuit Inc. | CHEN, KUANG FU | 2143 | §103§112 | Non-Final OA | — | Pending | Jun 14, 2024 |
| 18651543 | STREAMING DATA SET GENERATION FOR FINE-TUNING MODELS | Intuit, Inc. | ZATEZALO, MISHA DAYLA | §101§103 | Non-Final OA | — | Pending | Apr 30, 2024 | |
| 18592358 | EMBEDDED GENERATIVE AI-BASED DOMAIN EXPLANATIONS | Intuit, Inc. | LE, MICHAEL HOANG | 2141 | §103 | Non-Final OA | — | Pending | Feb 29, 2024 |
| 18592377 | ASSISTIVE GENERATIVE AI-BASED RESPONSES | Intuit, Inc. | VINCENT, DAVID ROBERT | 2123 | §101 | Non-Final OA | — | Pending | Feb 29, 2024 |
| 18424572 | SLANG USAGE DETECTION AND MITIGATION FOR LARGE LANGUAGE MODELS | Intuit, Inc. | TENGBUMROONG, NATHAN NARA | 2654 | §103 | Non-Final OA | 49d overdue | Pending | Jan 26, 2024 |
| 18497884 | AUTOMIZED GENERATION OF INSIGHTFUL AND CONFIDENT DATA INSIGHTS | Intuit, Inc. | ANNIS, PETER THOMAS | 4100 | §101§102§103 | Non-Final OA | — | Pending | Oct 30, 2023 |
| 18495172 | WORKFLOW ASSISTANT WITH GENERATIVE ARTIFICIAL INTELLIGENCE | Intuit, Inc. | PENG, STEVEN | 2125 | §101§102§103 | Non-Final OA | — | Pending | Oct 26, 2023 |
| 18372660 | EXPERT FEEDBACK LOOP FOR RESOLVING AMBIGUITY | Intuit, Inc. | ROY, SANCHITA | 2146 | §101§102§103§112 | Non-Final OA | — | Pending | Sep 25, 2023 |
IP Author helps law firms respond to office actions faster with AI-generated responses, examiner analytics, and prosecution intelligence.
Start Free Trial85.4% of resolved applications prosecuted by Dinsmore & Shohl LLP - Intuit were allowed, across 34,995 applications in USPTO records.
3.05 office actions per allowed application on average.
12 pending office actions as of October 2026, for 2 clients, before 12 examiners in 10 art units.
