Examiner Ababacar Seck has allowed 359 of 534 decided applications (67%) in Computer Architecture, Software, and Information Security.
Ababacar Seck maintains a public record across 3 art units within Technology Center 2100 (Computer Architecture, Software, and Information Security). Over 534 decided applications, the allowance rate stands at 67%, with 359 applications allowed and 175 abandoned. The allowance rate ranges from 64% to 75% across these art units. This pooled figure reflects outcomes across multiple examination areas within the technology center and does not predict results in any individual application.
A pooled record aggregates data across multiple art units, presenting an overall allowance rate that masks variation among those units. The range shown here reflects the lowest and highest allowance rates observed within the examiner's art units. These figures describe past dispositions and are correlational—they establish a historical baseline and do not forecast the outcome of any specific case or indicate how any particular application will be examined.
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 neural-network / biological-model computing, and machine learning.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 181 decided applications with an interview and 222 without.
Primarily examines artificial-intelligence and machine-learning methods.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 58 decided applications with an interview and 64 without.
Primarily examines neural-network / biological-model computing, and machine learning.
Based on 9 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Methodology. This page pools every art unit in which Examiner Ababacar Seck 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: 568 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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