- io.net launched its Training as a Service (TaaS) tool, offering developers a unified platform to train AI models and agents with any open-weight models from Hugging Face.
- The service addresses fragmentation in AI development by combining multiple training methods—supervised, reinforcement, preference-based, and unsupervised—in a single environment with full visibility into training progress.
- TaaS integrates with io.net’s broader AI toolkit, allowing one-click deployment from training to production while automatically hosting trained agents on HuggingFace for easy distribution.
Delaware, USA | 4pm UTC, 23rd July 2025: io.net, the intelligent stack for powering AI workloads, today launched its model and agent Training as a Service (TaaS) tool. Integrations with any open-weight models and datasets available on Hugging Face bring unparalleled flexibility, simplifying the agent and model training and deployment process for startups, engineers, enterprises and researchers alike.
Businesses and developers are excited about the new business models enabled by agents, with an IBM survey revealing that 99% of developers are exploring or developing AI agents. However, model and agent training is fragmented, with developers dependent on multiple tools which only support certain models and datasets. io.net’s TaaS employs a bring-your-own model approach, simplifying the training, experimentation and deployment process.
By supporting a suite of training paradigms, TaaS combines supervised, reinforcement, preference-based and unsupervised methods in a single environment, empowering users to iterate on a wide range of models within a single tool. Once users have configured their model or agent, the TaaS dashboard brings full visibility to training progress with interactive loss charts, checkpoint snapshots and training logs, improving troubleshooting and model understanding.
The TaaS tool is a key component of io.intelligence, io.net’s simple and comprehensive AI toolkit that also includes inferencing and a marketplace for models and agents. After training is completed with the TaaS tool, a one-click transition deploys models and agents from training to production. Agents are automatically hosted on HuggingFace for users to download and deploy with IO Cloud, any other cloud compute provider or run locally.
Gaurav Sharma, CEO of io.net, said: “The launch of our Training as a Service tool brings new functionality to engineers, enabling complete customization over LLM training workflows within a single intuitive interface. io.intelligence is the complete stack for developing models and agents; enabling users to train, deploy and share them within a unified platform.”
io.net’s TaaS tool supports modular optimization libraries, empowering researchers to reduce memory requirements, increase speed and improve agent fine-tuning behaviour through a range of advanced configurations. Researchers also benefit from multi-method experimentation tracking, centralizing all experiments in one place to simplify model comparison and team training.
The roadmap for io.net’s TaaS tool includes advanced training configurations, offering granular controls over many variables including learning rate, batch size and gradient accumulation, to enable fine-tuning of complex LLM (large language model) workflows. Automatic checkpointing will also be added, recording progress as users iteratively dial in their model or agent to ensure full ownership and reproducibility, letting users resume training at any time.
To start using Training as a Service for free today, click here.
Powered by the world’s largest network of decentralized, high-performance compute, io.net is the intelligent stack for powering AI workloads. Last month, IOG Foundation – an organization committed to supporting the growth of the io.net ecosystem – launched a grant program to accelerate compute-intensive AI innovation, offering free compute access to selected startups, researchers and developers through a share of 20 million $IO tokens. To apply, visit the website here.
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