PINKSWANTRADE Trademark
Serial Number: 98952463
Trademark Classes
Owner Contact Info
Legal Representation
Correspondence Address
Justin Johanson Rocket Legal Professional Services, Inc.
3137 E Elwood ST STE 130, DPT#EXAZ1394
Phoenix, AZ 85034
United States
Trademark Details
Filing Date
January 10, 2025
Registration Date
Not Registered
Published for Opposition
August 19, 2025
Goods & Services
Consultancy in the field of software design; Consultation services relating to computer software; Providing a web site featuring technology that enables users to develop financial software, software for use in creating statistical financial trading strategies, software for machine learning, and software using artificial intelligence; Providing a web site featuring technology that enables users to create statistical financial trading strategies; Software development consulting in the field of financial software, software for use in creating statistical financial trading strategies, software for machine learning, and software using artificial intelligence; Computer software consultancy; IT consulting services relating to installation, maintenance and repair of computer software; Platform as a service (PAAS) featuring computer software platforms for financial management and planning, and to enable users to evaluate investments and market trends for investment purposes; Platform as a service (PAAS) featuring computer software platforms for creating statistical financial trading strategies; Platform as a service (PAAS) featuring computer software platforms for collecting, analyzing and organizing data in the field of deep learning; Software as a service (SAAS) services featuring software for financial management and planning, and to enable users to evaluate investments and market trends for investment purposes; Software as a service (SAAS) services featuring software for creating statistical financial trading strategies; Software as a service (SAAS) services featuring software for collecting, analyzing and organizing data in the field of deep learning