Examiner Saif A Alhija has allowed 460 of 660 decided applications (70%) in Computer Architecture, Software, and Information Security.
Saif A Alhija maintains a public record across 3 art units in Technology Center 2100 (Computer Architecture, Software, and Information Security). Of 660 disposed applications, 460 were allowed, yielding a 70% allowance rate. The examiner's allowance rates across individual art units range from 66% to 92%, reflecting variation in prosecution outcomes within the technology center. This pooled record aggregates work across multiple art units and does not constitute a prediction for any specific application.
A pooled, cross-art-unit record aggregates an examiner's work across multiple art units into a single allowance statistic. The overall rate describes past dispositions and is not a prediction of how any individual application will be examined. Range figures show that allowance rates vary among the art units included in this examiner's record. Pooled data is useful context for understanding an examiner's overall record but does not forecast any particular case outcome.
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 machine learning, and neural-network / biological-model computing.
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 203 decided applications with an interview and 358 without.
Primarily examines computer-aided design (CAD).
Allowance rate for applications with an examiner interview versus without one.
A correlation, not proof that interviews cause allowances. Based on 34 decided applications with an interview and 57 without.
Primarily examines artificial-intelligence and machine-learning methods.
Based on 8 applications — too small a sample to characterize the rejection mix reliably; shown for completeness.
Methodology. This page pools every art unit in which Examiner Saif A Alhija 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: 720 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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