Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 19360280 | ATTENTION NEURAL NETWORKS WITH LINEAR UNITS | October 2025 | December 2025 | Allow | 2 | 0 | 0 | Yes | No |
| 19253802 | METHOD AND SYSTEM FOR NEURAL NETWORK CONFIDENCE REGULATION VIA TEMPERING FACTOR | June 2025 | November 2025 | Allow | 4 | 0 | 0 | Yes | No |
| 19241593 | DETECTION METHOD, SYSTEM, MEDIUM AND DEVICE BASED ON MULTI-SPECTRAL DATA FUSION | June 2025 | August 2025 | Allow | 2 | 0 | 0 | Yes | No |
| 19237528 | AUTOMATED TECHNOLOGIES FOR ASSESSING AND CERTIFYING THE SAFETY OF AI-BASED PRODUCTS BASED ON MACHINE LEARNING ANALYSIS | June 2025 | July 2025 | Allow | 2 | 0 | 0 | Yes | No |
| 19203278 | ANALOG AI COMPUTING ARCHITECTURE | May 2025 | July 2025 | Allow | 3 | 1 | 0 | No | No |
| 19175902 | TOPOLOGICAL ORDER DETERMINATION IN CAUSAL GRAPHS | April 2025 | June 2025 | Allow | 2 | 0 | 0 | Yes | No |
| 19085323 | ARTIFICIAL INTELLIGENCE MODEL GENERATED USING AGENTIC WORKFLOW SYSTEM AND METHOD FOR ARTIFICIAL INTELLIGENCE MODEL ALIGNED WITH DOMAIN-SPECIFIC PRINCIPLES | March 2025 | December 2025 | Allow | 9 | 1 | 0 | Yes | No |
| 19050755 | DETECTING AND REDUCING BIAS IN MACHINE LEARNING MODELS | February 2025 | August 2025 | Allow | 6 | 1 | 0 | Yes | No |
| 19046748 | SYSTEMS AND METHODS FOR INTELLIGENT GENERATION AND ASSESSMENT OF CANDIDATE LESS DISCRIMINATORY ALTERNATIVE MACHINE LEARNING MODELS | February 2025 | April 2025 | Allow | 2 | 0 | 0 | Yes | No |
| 19033441 | AUTOMATED TECHNOLOGIES FOR ASSESSING AND CERTIFYING THE SAFETY OF AI-BASED PRODUCTS BASED ON MACHINE LEARNING ANALYSIS | January 2025 | April 2025 | Allow | 3 | 0 | 0 | Yes | No |
| 19008444 | AGENTIC WORKFLOW SYSTEM AND METHOD FOR GENERATING SYNTHETIC DATA FOR TRAINING OR POST TRAINING ARTIFICIAL INTELLIGENCE MODELS TO BE ALIGNED WITH DOMAIN-SPECIFIC PRINCIPLES | January 2025 | February 2025 | Allow | 2 | 0 | 0 | Yes | No |
| 18969830 | METHOD AND SYSTEM FOR USING AI MODELS TO OPTIMIZE A GOAL | December 2024 | May 2025 | Allow | 5 | 1 | 0 | Yes | No |
| 18947502 | TOPOLOGICAL ORDER DETERMINATION IN CAUSAL GRAPHS | November 2024 | April 2025 | Allow | 5 | 1 | 0 | Yes | No |
| 18944178 | SYSTEMS AND METHODS FOR GENERATING CUSTOMIZED AI MODELS | November 2024 | April 2025 | Allow | 6 | 1 | 0 | Yes | No |
| 18934779 | EXPERIMENTAL CONTENT GENERATION LEARNING MODEL FOR RAPID MACHINE LEARNING IN A DATA-CONSTRAINED ENVIRONMENT | November 2024 | January 2025 | Allow | 2 | 0 | 0 | Yes | No |
| 18845615 | System, Method, and Computer Program Product for Reducing Dataset Biases in Natural Language Inference Tasks Using Unadversarial Training | September 2024 | February 2025 | Allow | 5 | 0 | 0 | Yes | No |
| 18824828 | SYSTEMS AND METHODS FOR OUTLIER DETECTION AND FEATURE TRANSFORMATION IN MACHINE LEARNING MODEL TRAINING | September 2024 | November 2024 | Allow | 2 | 0 | 0 | Yes | No |
| 18800900 | PROMPT ROUTING SYSTEM AND METHOD | August 2024 | March 2025 | Allow | 7 | 1 | 0 | Yes | No |
| 18741000 | SYSTEMS AND METHODS FOR INTELLIGENT GENERATION AND ASSESSMENT OF CANDIDATE LESS DISCRIMINATORY ALTERNATIVE MACHINE LEARNING MODELS | June 2024 | December 2024 | Allow | 6 | 1 | 0 | Yes | No |
| 18672889 | SYSTEMS AND METHODS FOR MANAGING, DISTRIBUTING AND DEPLOYING A RECURSIVE DECISIONING SYSTEM BASED ON CONTINUOUSLY UPDATING MACHINE LEARNING MODELS | May 2024 | April 2025 | Allow | 11 | 0 | 0 | Yes | No |
| 18665210 | EXPERIMENTAL CONTENT GENERATION LEARNING MODEL FOR RAPID MACHINE LEARNING IN A DATA-CONSTRAINED ENVIRONMENT | May 2024 | July 2024 | Allow | 2 | 0 | 0 | Yes | No |
| 18660605 | METHODS AND DEVICES IN PERFORMING A VISION TESTING PROCEDURE ON A PERSON | May 2024 | December 2025 | Allow | 19 | 4 | 0 | Yes | No |
| 18661377 | GRADIENT ADVERSARIAL TRAINING OF NEURAL NETWORKS | May 2024 | May 2025 | Allow | 12 | 0 | 0 | Yes | No |
| 18646104 | SYSTEMS AND METHODS FOR ALIGNING LARGE MULTIMODAL MODELS (LMMs) OR LARGE LANGUAGE MODELS (LLMs) WITH DOMAIN-SPECIFIC PRINCIPLES | April 2024 | November 2024 | Allow | 6 | 1 | 0 | Yes | No |
| 18641245 | SYSTEMS AND METHODS FOR INTRACORTICAL BRAIN MACHINE INTERFACE DECODING | April 2024 | April 2025 | Allow | 12 | 0 | 0 | Yes | No |
| 18638585 | GUARDRAIL MACHINE LEARNING MODEL FOR AUTOMATED SOFTWARE | April 2024 | November 2024 | Allow | 7 | 1 | 0 | No | No |
| 18627258 | COMPUTER-BASED SYSTEMS CONFIGURED TO AUTOMATICALLY GENERATE A INTERACTION SESSION BASED ON AN INTERNAL IDENTIFICATION TOKEN AND METHODS OF USE THEREOF | April 2024 | July 2024 | Allow | 3 | 0 | 0 | Yes | No |
| 18600520 | APPARATUS AND METHOD FOR DETERMINING A PROJECTED OCCURRENCE | March 2024 | July 2024 | Allow | 5 | 1 | 0 | Yes | No |
| 18599955 | SYSTEMS AND METHODS FOR ALIGNING LARGE MULTIMODAL MODELS (LMMs) OR LARGE LANGUAGE MODELS (LLMs) WITH DOMAIN-SPECIFIC PRINCIPLES | March 2024 | September 2024 | Allow | 6 | 1 | 0 | Yes | No |
| 18686563 | Method, System, and Computer Program Product for Synthetic Oversampling for Boosting Supervised Anomaly Detection | February 2024 | July 2024 | Allow | 4 | 0 | 0 | Yes | No |
| 18428299 | CREATING A MACHINE LEARNING POLICY BASED ON EXPRESS INDICATORS | January 2024 | September 2024 | Allow | 8 | 0 | 0 | Yes | No |
| 18404365 | QUANTUM STATISTIC MACHINE | January 2024 | September 2024 | Allow | 9 | 0 | 0 | Yes | No |
| 18393349 | Counterfactual Policy Evaluation of Model Performance | December 2023 | January 2025 | Allow | 13 | 1 | 0 | Yes | No |
| 18538536 | ANONYMOUS TRAINING OF A LEARNING MODEL | December 2023 | January 2026 | Abandon | 25 | 1 | 0 | No | No |
| 18518412 | SYSTEM AND METHOD FOR FAULT DETECTION OF COMPONENTS USING INFORMATION FUSION TECHNIQUE | November 2023 | October 2025 | Allow | 22 | 1 | 0 | Yes | No |
| 18516405 | System, Apparatus and Method for Supporting Formal Verification of Informal Inference on a Computer | November 2023 | November 2025 | Abandon | 24 | 1 | 0 | No | No |
| 18514202 | VERIFYING THE PROVENANCE OF A MACHINE LEARNING SYSTEM | November 2023 | April 2024 | Allow | 5 | 1 | 0 | Yes | No |
| 18511672 | METHOD FOR DETERMINING AN UNCERTAINTY LEVEL OF DEEP REINFORCEMENT LEARNING NETWORK AND DEVICE IMPLEMENTING SUCH METHOD | November 2023 | May 2024 | Allow | 6 | 1 | 0 | Yes | No |
| 18503108 | PREDICTING USER STATE USING MACHINE LEARNING | November 2023 | May 2025 | Allow | 18 | 1 | 0 | No | No |
| 18386015 | TRAINING ENCODER MODEL AND/OR USING TRAINED ENCODER MODEL TO DETERMINE RESPONSIVE ACTION(S) FOR NATURAL LANGUAGE INPUT | November 2023 | April 2025 | Allow | 17 | 1 | 0 | Yes | No |
| 18494986 | DROP IMPACT PREDICTION METHOD AND SYSTEM FOR HEAVY EQUIPMENT AIRDROP BASED ON NEURAL NETWORK | October 2023 | February 2024 | Allow | 4 | 1 | 0 | Yes | No |
| 18493524 | Detecting and Correcting Anomalies in Computer-Based Reasoning Systems | October 2023 | September 2024 | Allow | 10 | 0 | 0 | Yes | No |
| 18483294 | CLUSTERING, EXPLAINABILITY, AND AUTOMATED DECISIONS IN COMPUTER-BASED REASONING SYSTEMS | October 2023 | June 2024 | Allow | 8 | 0 | 0 | Yes | No |
| 18464473 | DETECTION AND VISUALIZATION OF NOVEL DATA INSTANCES FOR SELF-HEALING AI/ML MODEL-BASED SOLUTION DEPLOYMENT | September 2023 | November 2025 | Allow | 26 | 2 | 0 | Yes | No |
| 18347408 | Explainable and Automated Decisions in Computer-Based Reasoning Systems | July 2023 | March 2024 | Allow | 9 | 0 | 0 | Yes | No |
| 18217290 | METROLOGY IN THE PRESENCE OF CMOS UNDER ARRAY (CUA) STRUCTURES UTILIZING MACHINE LEARNING AND PHYSICAL MODELING | June 2023 | April 2025 | Allow | 21 | 0 | 0 | Yes | No |
| 18196470 | ARCHITECTURES, SYSTEMS AND METHODS HAVING SEGREGATED SECURE AND PUBLIC FUNCTIONS | May 2023 | January 2024 | Allow | 8 | 1 | 0 | Yes | No |
| 18195876 | Reducing Parasitic Interactions in a Qubit Grid | May 2023 | February 2026 | Allow | 34 | 0 | 0 | Yes | No |
| 18311670 | HARDWARE-ASSISTED GRADIENT OPTIMIZATION USING STREAMED GRADIENTS | May 2023 | March 2025 | Allow | 22 | 1 | 0 | Yes | No |
| 18307748 | NEURAL NETWORK FOR PROCESSING APTAMER DATA | April 2023 | February 2025 | Allow | 21 | 1 | 0 | Yes | No |
| 18181529 | Detecting and Correcting Anomalies in Computer-Based Reasoning Systems | March 2023 | July 2023 | Allow | 4 | 0 | 0 | Yes | No |
| 18179132 | APPARATUS FOR CLASSIFYING DATA AND METHOD THEREOF | March 2023 | February 2026 | Allow | 35 | 0 | 0 | Yes | No |
| 18043155 | GENERATION METHOD, PROGRAM, INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND TRAINED MODEL | February 2023 | March 2024 | Allow | 12 | 2 | 0 | Yes | No |
| 18174275 | SCHEDULING CONFIGURATION FOR DEEP LEARNING NETWORKS | February 2023 | March 2024 | Allow | 12 | 1 | 0 | No | No |
| 18041857 | BIG DATA-BASED MODULAR AI ENGINE SERVER AND DRIVING METHOD OF THE SAME | February 2023 | October 2025 | Allow | 32 | 0 | 0 | Yes | No |
| 18102300 | SYSTEM AND METHOD FOR PROBABILISTIC DECISION-MAKING UNDER UNCERTAINTY IN AUTONOMOUS CYBER OPERATIONS | January 2023 | October 2025 | Allow | 33 | 0 | 0 | Yes | No |
| 18100290 | APPARATUS AND METHODS FOR QUANTUM COMPUTING AND MACHINE LEARNING | January 2023 | February 2024 | Allow | 13 | 1 | 0 | Yes | No |
| 18154674 | METHOD AND SYSTEM FOR SYNTHESIZING PHENOMENON DATA USING ARTIFICIAL INTELLIGENCE | January 2023 | September 2025 | Allow | 33 | 0 | 0 | Yes | No |
| 18153010 | DETECTION AND VISUALIZATION OF NOVEL DATA INSTANCES FOR SELF-HEALING AI/ML MODEL-BASED SOLUTION DEPLOYMENT | January 2023 | May 2023 | Allow | 5 | 1 | 0 | Yes | No |
| 18084920 | MACHINE LEARNING SYSTEM AND MACHINE LEARNING METHOD | December 2022 | February 2026 | Allow | 38 | 1 | 0 | Yes | No |
| 18066270 | ENABLING CLASSICAL PLANNING IN INTERACTIVE ENVIRONMENTS WITH INCOMPLETE MODELS | December 2022 | February 2026 | Allow | 38 | 1 | 0 | Yes | No |
| 17994672 | LEARNING DATA GENERATION SYSTEM, LEARNING DATA GENERATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM | November 2022 | August 2025 | Allow | 33 | 0 | 0 | Yes | No |
| 18058053 | MACHINE LEARNING PIPELINE AUTOMATION | November 2022 | January 2026 | Allow | 37 | 1 | 0 | Yes | No |
| 18056379 | DISTRIBUTED MACHINE LEARNING COMPILER OPTIMIZATION | November 2022 | August 2025 | Allow | 33 | 0 | 0 | Yes | No |
| 17975358 | VALIDATION OF ACCOUNT IDENTIFIER | October 2022 | August 2023 | Allow | 10 | 2 | 0 | Yes | No |
| 17963819 | FAILURE PREDICTOR DETECTION DEVICE, FAILURE PREDICTOR DETECTION METHOD, TRAINING DEVICE, AND TRAINED LEARNING MODEL GENERATION METHOD | October 2022 | November 2025 | Allow | 47 | 1 | 0 | Yes | No |
| 17962820 | Clustering, Explainability, and Automated Decisions in Computer-Based Reasoning Systems | October 2022 | July 2023 | Allow | 9 | 0 | 0 | Yes | No |
| 17937745 | Multiplicative Recurrent Neural Network for Fast and Robust Intracortical Brain Machine Interface Decoders | October 2022 | January 2024 | Allow | 15 | 1 | 0 | Yes | No |
| 17936677 | CORRECTING A MACHINE LEARNING MODEL | September 2022 | January 2026 | Allow | 39 | 1 | 0 | Yes | No |
| 17935217 | Method and System for Analyzing Data in a Database | September 2022 | February 2024 | Allow | 17 | 1 | 0 | Yes | No |
| 17945335 | SYSTEMS AND METHOD FOR AUTOMATING DETECTION OF REGIONS OF MACHINE LEARNING SYSTEM UNDERPERFORMANCE | September 2022 | October 2023 | Allow | 13 | 2 | 0 | Yes | No |
| 17930511 | SYSTEMS AND METHODS FOR MANAGING, DISTRIBUTING AND DEPLOYING A RECURSIVE DECISIONING SYSTEM BASED ON CONTINUOUSLY UPDATING MACHINE LEARNING MODELS | September 2022 | March 2024 | Allow | 18 | 1 | 0 | Yes | No |
| 17896281 | AUTOMATED PROCESSING OF MULTIPLE PREDICTION GENERATION INCLUDING MODEL TUNING | August 2022 | March 2024 | Allow | 18 | 1 | 0 | Yes | No |
| 17888742 | DIGITAL RIGHTS MANAGEMENT OF MACHINE LEARNING MODELS | August 2022 | January 2026 | Allow | 41 | 1 | 0 | Yes | No |
| 17811350 | METHOD FOR INTELLIGENT DISASTER AND SAFETY MANAGEMENT INTERWORKING WITH ARTIFICIAL INTELLIGENCE, AND SYSTEM FOR PERFORMING METHOD | July 2022 | March 2026 | Abandon | 44 | 1 | 0 | No | No |
| 17858980 | DEVICE, COMPUTER PROGRAM AND COMPUTER-IMPLEMENTED METHOD FOR MACHINE LEARNING | July 2022 | November 2025 | Allow | 40 | 1 | 0 | Yes | No |
| 17857204 | INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD | July 2022 | June 2025 | Abandon | 35 | 0 | 0 | No | No |
| 17810198 | MACHINE LEARNING MAPPING FOR QUANTUM PROCESSING UNITS | June 2022 | January 2024 | Allow | 19 | 1 | 0 | Yes | No |
| 17845291 | NEURAL NETWORK INSTRUCTION SET ARCHITECTURE | June 2022 | March 2024 | Allow | 21 | 1 | 0 | Yes | No |
| 17748743 | SYSTEM AND METHOD FOR HETEROGENEOUS MODEL COMPOSITION | May 2022 | January 2024 | Allow | 20 | 1 | 0 | Yes | No |
| 17773917 | GAP-AWARE MITIGATION OF GRADIENT STALENESS | May 2022 | January 2023 | Allow | 9 | 1 | 0 | Yes | No |
| 17720737 | CREATING A MACHINE LEARNING POLICY BASED ON EXPRESS INDICATORS | April 2022 | October 2023 | Allow | 19 | 1 | 0 | Yes | No |
| 17702286 | PREDICTIVE ANALYTICS USING FIRST-PARTY DATA OF LONG-TERM CONVERSION ENTITIES | March 2022 | October 2022 | Allow | 7 | 2 | 0 | Yes | No |
| 17696809 | PROBABILISTIC PROJECTION OF NETWORK PARAMETERS | March 2022 | October 2025 | Allow | 43 | 1 | 0 | Yes | No |
| 17696819 | ACCOUNTING FOR COMPUTE TIME IN TRAINING OF NETWORK | March 2022 | November 2025 | Allow | 44 | 1 | 0 | Yes | No |
| 17696812 | DECOMPOSITION OF WEIGHT TENSORS FOR STRUCTURAL SPARSITY | March 2022 | November 2025 | Allow | 44 | 1 | 0 | Yes | No |
| 17686072 | Artificial Intelligence/Machine Learning Model Decisioning and Rectification System | March 2022 | September 2025 | Allow | 42 | 1 | 0 | Yes | No |
| 17682200 | INDIVIDUAL TREATMENT EFFECT ESTIMATION UNDER HIGH-ORDER INTERFERENCE IN HYPERGRAPHS | February 2022 | March 2023 | Allow | 13 | 0 | 1 | Yes | No |
| 17678897 | QUANTUM STATISTIC MACHINE | February 2022 | October 2023 | Allow | 19 | 1 | 0 | Yes | No |
| 17668229 | AUGMENTATION OF SENSOR DATA UNDER VARIOUS WEATHER CONDITIONS TO TRAIN MACHINE-LEARNING SYSTEMS | February 2022 | March 2026 | Abandon | 49 | 2 | 0 | Yes | No |
| 17666442 | SYSTEMS FOR CONSTRUCTING HIERARCHICAL TRAINING DATA SETS FOR USE WITH MACHINE-LEARNING AND RELATED METHODS THEREFOR | February 2022 | October 2023 | Allow | 20 | 1 | 0 | Yes | No |
| 17649852 | VIRTUAL NOSE USING QUANTUM MACHINE LEARNING AND QUANTUM SIMULATION | February 2022 | June 2025 | Allow | 41 | 1 | 0 | Yes | No |
| 17590181 | Systems and Methods for Managing, Distributing and Deploying a Recursive Decisioning System Based on Continuously Updating Machine Learning Models | February 2022 | August 2022 | Allow | 7 | 1 | 0 | Yes | No |
| 17587806 | AUTOMATED PROCESSING OF MULTIPLE PREDICTION GENERATION INCLUDING MODEL TUNING | January 2022 | May 2022 | Allow | 4 | 1 | 0 | Yes | No |
| 17627835 | METHOD AND DEVICE FOR DETECTING ANOMALIES, CORRESPONDING COMPUTER PROGRAM AND NON-TRANSITORY COMPUTER-READABLE MEDIUM | January 2022 | September 2025 | Abandon | 44 | 1 | 0 | No | No |
| 17570784 | NEURAL NETWORK ACCELERATOR TILE ARCHITECTURE WITH THREE-DIMENSIONAL STACKING | January 2022 | January 2024 | Allow | 25 | 1 | 0 | Yes | No |
| 17560816 | MACHINE LEARNING MAPPING FOR QUANTUM PROCESSING UNITS | December 2021 | June 2022 | Allow | 6 | 1 | 0 | Yes | No |
| 17524161 | Explainable and Automated Decisions in Computer-Based Reasoning Systems | November 2021 | April 2023 | Allow | 17 | 0 | 0 | Yes | No |
| 17498978 | TARGET DATA PARTY SELECTION METHODS AND SYSTEMS FOR DISTRIBUTED MODEL TRAINING | October 2021 | May 2022 | Allow | 7 | 1 | 0 | Yes | No |
| 17497529 | ANONYMOUS TRAINING OF A LEARNING MODEL | October 2021 | May 2024 | Abandon | 31 | 2 | 0 | No | Yes |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner MISIR, DAYWAYSHWAR D.
With a 50.0% reversal rate, the PTAB reverses the examiner's rejections in a meaningful percentage of cases. This reversal rate is above the USPTO average, indicating that appeals have better success here than typical.
Filing a Notice of Appeal can sometimes lead to allowance even before the appeal is fully briefed or decided by the PTAB. This occurs when the examiner or their supervisor reconsiders the rejection during the mandatory appeal conference (MPEP § 1207.01) after the appeal is filed.
In this dataset, 33.3% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is above the USPTO average, suggesting that filing an appeal can be an effective strategy for prompting reconsideration.
✓ Appeals to PTAB show good success rates. If you have a strong case on the merits, consider fully prosecuting the appeal to a Board decision.
✓ Filing a Notice of Appeal is strategically valuable. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.
Examiner MISIR, DAYWAYSHWAR D works in Art Unit 2127 and has examined 148 patent applications in our dataset. With an allowance rate of 81.1%, this examiner has an above-average tendency to allow applications. Applications typically reach final disposition in approximately 41 months.
Examiner MISIR, DAYWAYSHWAR D's allowance rate of 81.1% places them in the 52% percentile among all USPTO examiners. This examiner has an above-average tendency to allow applications.
On average, applications examined by MISIR, DAYWAYSHWAR D receive 1.55 office actions before reaching final disposition. This places the examiner in the 29% percentile for office actions issued. This examiner issues fewer office actions than average, which may indicate efficient prosecution or a more lenient examination style.
The median time to disposition (half-life) for applications examined by MISIR, DAYWAYSHWAR D is 41 months. This places the examiner in the 21% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +51.7% benefit to allowance rate for applications examined by MISIR, DAYWAYSHWAR D. This interview benefit is in the 94% percentile among all examiners. Recommendation: Interviews are highly effective with this examiner and should be strongly considered as a prosecution strategy. Per MPEP § 713.10, interviews are available at any time before the Notice of Allowance is mailed or jurisdiction transfers to the PTAB.
When applicants file an RCE with this examiner, 27.0% of applications are subsequently allowed. This success rate is in the 46% percentile among all examiners. Strategic Insight: RCEs show below-average effectiveness with this examiner. Carefully evaluate whether an RCE or continuation is the better strategy.
This examiner enters after-final amendments leading to allowance in 5.6% of cases where such amendments are filed. This entry rate is in the 6% percentile among all examiners. Strategic Recommendation: This examiner rarely enters after-final amendments compared to other examiners. You should generally plan to file an RCE or appeal rather than relying on after-final amendment entry. Per MPEP § 714.12, primary examiners have discretion in entering after-final amendments, and this examiner exercises that discretion conservatively.
When applicants request a pre-appeal conference (PAC) with this examiner, 50.0% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 43% percentile among all examiners. Note: Pre-appeal conferences show below-average success with this examiner. Consider whether your arguments are strong enough to warrant a PAC request.
This examiner withdraws rejections or reopens prosecution in 50.0% of appeals filed. This is in the 15% percentile among all examiners. Of these withdrawals, 25.0% occur early in the appeal process (after Notice of Appeal but before Appeal Brief). Strategic Insight: This examiner rarely withdraws rejections during the appeal process compared to other examiners. If you file an appeal, be prepared to fully prosecute it to a PTAB decision. Per MPEP § 1207, the examiner will prepare an Examiner's Answer maintaining the rejections.
When applicants file petitions regarding this examiner's actions, 38.7% are granted (fully or in part). This grant rate is in the 27% percentile among all examiners. Strategic Note: Petitions show below-average success regarding this examiner's actions. Ensure you have a strong procedural basis before filing.
Examiner's Amendments: This examiner makes examiner's amendments in 0.0% of allowed cases (in the 9% percentile). This examiner rarely makes examiner's amendments compared to other examiners. You should expect to make all necessary claim amendments yourself through formal amendment practice.
Quayle Actions: This examiner issues Ex Parte Quayle actions in 5.0% of allowed cases (in the 80% percentile). Per MPEP § 714.14, a Quayle action indicates that all claims are allowable but formal matters remain. This examiner frequently uses Quayle actions compared to other examiners, which is a positive indicator that once substantive issues are resolved, allowance follows quickly.
Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:
Not Legal Advice: The information provided in this report is for informational purposes only and does not constitute legal advice. You should consult with a qualified patent attorney or agent for advice specific to your situation.
No Guarantees: We do not provide any guarantees as to the accuracy, completeness, or timeliness of the statistics presented above. Patent prosecution statistics are derived from publicly available USPTO data and are subject to data quality limitations, processing errors, and changes in USPTO practices over time.
Limitation of Liability: Under no circumstances will IronCrow AI be liable for any outcome, decision, or action resulting from your reliance on the statistics, analysis, or recommendations presented in this report. Past prosecution patterns do not guarantee future results.
Use at Your Own Risk: While we strive to provide accurate and useful prosecution statistics, you should independently verify any information that is material to your prosecution strategy and use your professional judgment in all patent prosecution matters.