Examiner Anil Khatri has allowed 1,181 of 1,286 decided applications (92%) in Computer Architecture, Software, and Information Security.
Examiner Anil Khatri maintains a public record across five art units within Technology Center 2100 (Computer Architecture, Software, and Information Security). Over 1,286 disposed applications, the pooled allowance rate is 92%, with 1,181 allowed and 105 abandoned. The allowance rate ranges from 74% to 97% across the art units in which he maintains a substantial record. This aggregate figure reflects decided applications only and does not account for pending filings.
A pooled record aggregates data across multiple art units, creating a composite picture rather than unit-specific performance. The 92% allowance rate describes historical outcomes across all units combined and is not a prediction of any specific application's outcome. Ranges reflect variation among individual art units; the aggregate masks this variation. Pooled figures are most useful for understanding overall record breadth and past disposition patterns.
These are aggregate statistics from this examiner's past public record — not predictions about any specific application. The per-art-unit figures below show how the record varies across art units. Our approach to patent prosecution →
Each section benchmarks this examiner against that art unit's average. Figures are this examiner's own public record within the art unit; the overall rate above pools them.
Primarily examines software engineering, and error detection, correction, and monitoring.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 755 decided applications with an interview and 408 without.
Primarily examines program control and execution, and software engineering.
Primarily examines software engineering, and error detection, correction, and monitoring.
Primarily examines neural-network / biological-model computing, and machine learning.
Primarily examines neural-network / biological-model computing, and machine learning.
Methodology. This page pools every art unit in which Examiner Anil Khatri has a public record within Technology Center 2100. Statistics are computed from publicly available USPTO records, refreshed on a recurring schedule. This page's data was last updated June 25, 2026. The overall allowance rate is total allowed divided by total decided applications (allowed plus abandoned) across all art units — not an average of the per-art-unit rates; pending applications are excluded. Figures are rounded for display. Pooled sample: 1,308 applications.
Lynch LLP is not affiliated with, endorsed by, or sponsored by the United States Patent and Trademark Office. Examiner statistics are derived from publicly available USPTO data.
These statistics describe past examiner behavior and do not predict the outcome of any particular application. Past results do not guarantee future outcomes. Where this page compares an examiner's allowance rate to an art-unit average, that comparison is a factual description of the public record, not a characterization of any individual examiner's conduct or competence.
This page is for general informational purposes and is not legal advice. No attorney-client relationship is formed by viewing it. Full disclaimers →
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