CERNA ADAPTIVE PERCEPTION
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Serial Number

50107330

Owner

ML OPS WORKBENCH LLC

Attorney

Sarah I Cohen

Filing Date

Sep 14, 2026

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CERNA ADAPTIVE PERCEPTION Trademark

Serial Number: 50107330

CERNA ADAPTIVE PERCEPTION is a trademark filed by ML OPS WORKBENCH LLC on September 14, 2026. The trademark is classified under Class 9 (Computers & Electronics), Class 42 (Computer & Scientific). The application is currently pending registration.

Owner Contact Info

ML OPS WORKBENCH LLC (5 trademarks)

355 Lexington Ave Ste 1220
NYC, NY 10017

Entity Type: 16

Trademark Details

Filing Date

September 14, 2026

Registration Date

Not Registered

Goods & Services

Computer services, namely, hosting, managing, maintaining, and operating software platforms and applications of others for data processing, analytics, and machine learning;; Application service provider services, namely, hosting software for use by others for data integration, workflow execution, synchronization, and interoperability between cloud-based and on-premises systems; Software as a service (SAAS) services and platform as a service (PAAS) services providing computer software and software platforms for use in data ingestion, data storage, data management, data processing, data integration, data warehousing, data analytics, and machine learning, for developing, training, evaluating, deploying, and operating analytical models and machine learning models, for managing clustered file systems, data catalogs, metadata repositories, and data access controls, for machine perception and robotic perception, for processing, analyzing, integrating and interpreting data from cameras, event-based vision sensors and other sensors, for sensor fusion, for object detection, recognition, classification, localization and tracking, for scene understanding, motion estimation and environmental perception, for orchestrating compute workloads, routing execution, managing software development environments, and governing computer usage across distributed computing infrastructure, for dynamically selecting, configuring or modifying sensors, perception algorithms, machine learning models and data processing parameters based on environmental conditions, task requirements and system state, for developing, testing, simulating, training, deploying and operating perception systems for robots, autonomous machines and intelligent devices

Downloadable computer software, downloadable cloud-enabled computer software, and downloadable computer software platforms for use in data ingestion, data storage, data management, data processing, data integration, data warehousing, data analytics, and machine learning, for orchestrating compute workloads, routing execution, managing storage resources, enforcing security and access controls, and integrating data and compute environments across cloud and on-premises infrastructure, for developing, training, evaluating, deploying, and operating analytical models and machine learning models, for managing clustered file systems, data catalogs, and metadata repositories, for enabling controlled development environments, governance of compute usage, administrative delegation, auditing, and compliance, for machine perception and robotic perception, for processing, analyzing, integrating and interpreting data from cameras, event-based vision sensors and other sensors, for sensor fusion, for object detection, recognition, classification, localization and tracking, scene understanding, motion estimation and environmental perception, for dynamically selecting, configuring or modifying sensors, perception algorithms, machine learning models and data processing parameters based on environmental conditions, task requirements and system state, for developing, testing, training, deploying and operating perception systems for robots, autonomous machines and intelligent devices, for integrating and synchronizing data, workflows, and applications across heterogeneous systems

Filing History

APPLICATION FILING RECEIPT MAILED
Sep 14, 2026 MAFR
NEW APPLICATION ENTERED
Sep 14, 2026 NWAP