Trademark Overview
On Friday, February 13, 2026, a trademark application was filed for CORELAYER with the United States Patent and Trademark Office. The USPTO has given the CORELAYER trademark a serial number of 99651174. The federal status of this trademark filing is NEW APPLICATION - RECORD INITIALIZED NOT ASSIGNED TO EXAMINER as of Friday, February 13, 2026. This trademark is owned by Sevvy AI, Inc.. The CORELAYER trademark is filed in the Computer & Software Products & Electrical & Scientific Products and Computer & Software Services & Scientific Services categories with the following description:
Downloadable workflow management software; Downloadable computer software for real-time monitoring, observability, and performance analysis of engineering production systems, and collection and analysis of metrics, logs, and traces; Downloadable computer software for incident detection, alerting, troubleshooting, and root cause analysis in engineering production environments; Downloadable computer software platforms for engineering production support and operations; Downloadable computer software using artificial intelligence (AI) for monitoring, analyzing, and correlating production data and infrastructure metrics, detecting and diagnosing issues, and generating recommendations and decision support for debugging and resolving problems in engineering production environments
Software as a service (SAAS) services featuring software for real-time monitoring, observability, and performance analysis of engineering production systems, and collection and analysis of metrics, logs, and traces; Providing online non-downloadable workflow management software; Providing on-line non-downloadable software for incident detection, alerting, troubleshooting, and root cause analysis in engineering production environments; Providing online non-downloadable computer software platforms for engineering production support and operations; Providing on-line non-downloadable software using artificial intelligence (AI) for monitoring, analyzing, and correlating production data and infrastructure metrics, detecting and diagnosing issues, and generating recommendations and decision support for debugging and resolving problems in engineering production environments