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features
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support

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Description

ReinforceNow serves as a comprehensive platform dedicated to ongoing learning through AI agents, designed to assist teams in deploying, training, and iterating efficiently. Developers are empowered to create AI agents that can be continuously trained using production traffic, or they can opt for Claude Code to configure the setup automatically. The platform manages vital components such as reinforcement learning infrastructure, experiment orchestration, agent versioning, GPU training logic, and telemetry, allowing teams to concentrate on refining agent logic, data collection, and reward systems. With support for rapid LLM fine-tuning using LoRA, high-throughput training capabilities, and extensive compatibility with open-source models including Qwen, DeepSeek, and GPT-OSS, ReinforceNow enhances developers' efficiency. It offers sophisticated telemetry features that help evaluate, monitor, and iterate on AI agent LLM applications, including detailed traces, reward systems, experiment metrics, and training visibility. Teams can tackle extended tasks that require context sizes ranging from 32k to 1 million, create specialized agents for multi-turn interactions and long-duration tasks, and access an array of tools to streamline their reinforcement learning workflows, ultimately fostering innovation in AI development.

Description

TensorFlow Agents (TF-Agents) is an extensive library tailored for reinforcement learning within the TensorFlow framework. It streamlines the creation, execution, and evaluation of new RL algorithms by offering modular components that are both reliable and amenable to customization. Through TF-Agents, developers can quickly iterate on code while ensuring effective test integration and performance benchmarking. The library features a diverse range of agents, including DQN, PPO, REINFORCE, SAC, and TD3, each equipped with their own networks and policies. Additionally, it provides resources for crafting custom environments, policies, and networks, which aids in the development of intricate RL workflows. TF-Agents is designed to work seamlessly with Python and TensorFlow environments, presenting flexibility for various development and deployment scenarios. Furthermore, it is fully compatible with TensorFlow 2.x and offers extensive tutorials and guides to assist users in initiating agent training on established environments such as CartPole. Overall, TF-Agents serves as a robust framework for researchers and developers looking to explore the field of reinforcement learning.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) Yes 
Claude Code Yes 
DeepSeek Yes 
Google Cloud Platform Yes 
Python No 
Qwen Yes 
Runpod Yes 
TensorFlow No 
gpt-oss-120b Yes 

Integrations

Amazon Web Services (AWS) No 
Claude Code No 
DeepSeek No 
Google Cloud Platform No 
Python Yes 
Qwen No 
Runpod No 
TensorFlow Yes 
gpt-oss-120b No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

ReinforceNow

Country

United States

Website

www.reinforcenow.ai/

Vendor Details

Company Name

Tensorflow

Founded

2015

Country

United States

Website

www.tensorflow.org/agents

Product Features

Product Features

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