The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Apr. 14, 2026
Filed:
Aug. 25, 2025
Citibank, N.a., New York, NY (US);
Ganesh Prasad Bhat, New Jersey, NJ (US);
James Myers, New York, NY (US);
Zheyu Wang, Shanghai, CN;
Haolin Jin, Shanghai, CN;
Sourabh Deb, Tampa, FL (US);
Jason Ryan Engelbrecht, London, GB;
Payal Jain, London, GB;
Tariq Husayn Maonah, London, GB;
Mariusz Saternus, Cracow, PL;
Daniel Lewandowski, Cracow, PL;
Biraj Krushna Rath, London, GB;
Stuart Murray, London, GB;
Philip Davies, London, GB;
Julisia Jackson, Irving, TX (US);
Chamindra Desilva, London, GB;
Shardul Malviya, London, GB;
Wayne Liao, London, GB;
Deepak Jain, London, GB;
Samantha Cory, London, GB;
Vishal Mysore, Mississauga, CA;
Ramkumar Ayyadurai, Jersey City, NJ (US);
Abstract
Systems, methods, and devices that relate to intelligent query decomposition and parallel routing for specialized model processing are disclosed. In one example aspect, the system receives a query from a user comprising a request relating to a particular domain. The system determines, using a decomposition model, a set of sub-queries based on semantic boundaries, syntactics, tasks, relationships, and rules relating to particular domains. The system inputs the set of sub-queries into a routing model to determine a set of specialized models. For each sub-query, the system routes the sub-query to a respective specialized model, generates an output, and assigns a confidence score. The system detects conflicts among outputs using a conflict detection model configured to identify discrepancies. The system generates an aggregated output by combining outputs according to a weighted aggregation algorithm prioritizing higher confidence scores and conflict resolution rules, then displays the aggregated output.