Serial Number
88336592
Owner
Austin Data Labs, Inc.Attorney
Brett Albert SchenckFiling Date
Mar 12, 2019
AUSTIN LABS Trademark
Serial Number: 88336592 • Registration: 5935749
Trademark Classes
Owner Contact Info
Legal Representation
Correspondence Address
Brett Albert Schenck SCHENCK LAW OFFICE
49 SOUTH LADUE ESTATES DRIVE
CREVE COEUR, MO 63141
UNITED STATES
Trademark Details
Filing Date
March 12, 2019
Registration Date
December 17, 2019
Published for Opposition
October 1, 2019
Cancellation Date
July 3, 2026
Goods & Services
Providing temporary use of on-line non-downloadable cloud computing software for structuring and storing knowledge and enterprise business data for use in machine learning, data science, and predictive modeling based applications, namely, supply chain optimization applications for production, optimization, price and margin optimization, sales and operations planning, sales analysis, product deployment and scheduling, price and demand forecasting; providing temporary use of on-line non-downloadable cloud computing software for structuring and storing knowledge and enterprise business data for use in predictive modeling applications and IoT internet of things applications, namely, applications that analyze functionality and maintenance requirements for manufacturing equipment, turbine pumps, rotary pumps, piston pumps, top drive drill motors, aircraft engines, diesel engines, and gasoline engines; consulting services in the field of software as a service (SAAS); design and development of computer software; Platform-as-a-Service (PaaS) featuring software for structuring and storing knowledge and enterprise business data for use in machine learning, data science, and predictive modeling based applications, namely, supply chain optimization applications for production, optimization, price and margin optimization, sales and operations planning, sales analysis, product deployment and scheduling, price and demand forecasting; Platform-as-a-Service (PaaS) featuring software for structuring and storing knowledge and enterprise business data for use in predictive modeling applications and IoT internet of things applications, namely, applications that analyze functionality and maintenance requirements for manufacturing equipment, turbine pumps, rotary pumps, piston pumps, top drive drill motors, aircraft engines, diesel engines, and gasoline engines