AGILERL ARENA
Summary of public USPTO data
- Owner
- AGILERL INC.
- Status
- Live/Registered
- Serial number
- 99707145
- Registration number
- 8484425
- Filing date
- 2026-03-17
- Registration date
- 2026-10-06
- International classes
- 42
Goods and services
Class 42
- Providing temporary use of online, non-downloadable computer software for managing the full reinforcement learning (RL) lifecycle, namely, building, training, scaling, monitoring, and deploying artificial intelligence (AI) agents
- Providing temporary use of online, non-downloadable computer software for building, training, scaling, monitoring, and deploying reinforcement learning (RL) workloads and applications
- Providing temporary use of online, non-downloadable computer software featuring a reinforcement learning operations (RLOs) platform
- Providing temporary use of online, non-downloadable computer software for automatic tuning of any single- and multi-agent task
- Providing temporary use of online, non-downloadable computer software for fine-tuning large language models (LLMs) using hyperparameter optimization (HPO) and one-click deployment
- Providing temporary use of online, non-downloadable computer software for validating datasets and environments before training artificial intelligence (AI) agents
- Providing temporary use of online, non-downloadable computer software for selecting algorithms, rewards, constraints, and objectives to configure artificial intelligence (AI) agents
- Providing temporary use of online, non-downloadable computer software for distributing artificial intelligence (AI) agents across multiple graphic processing units (GPUs) and for monitoring metrics, sampling efficiency, and providing checkpoints in real time
- Providing temporary use of online, non-downloadable computer software for promoting a model from a testing environment to a live production environment with one click
- Providing temporary use of online, non-downloadable computer software for monitoring and tracking artificial intelligence (AI) agent performance, executing instant roll backs, and iterating through training credits