Agentic-IAM leverages a large language model to transform natural language prompts into AWS identity and access management configurations. Users describe desired roles, permissions, and security requirements in plain English, and the agent crafts least-privilege IAM policies, builds CloudFormation templates, flags potential vulnerabilities, and optionally deploys changes via AWS APIs. Policy drafts can be reviewed, refined, and versioned automatically. Integration with AWS CLI and SDK ensures seamless end-to-end automation of IAM tasks, from initial design through application and audit.

TensorBlock is designed to simplify the machine learning journey by offering elastic GPU clusters, integrated MLOps pipelines, and flexible deployment options. With a focus on ease of use, it allows data scientists and engineers to spin up CUDA-enabled instances in seconds for model training, manage datasets, track experiments, and automatically log metrics. Once models are trained, users can deploy them as scalable RESTful endpoints, schedule batch inference jobs, or export Docker containers. The platform also includes role-based access controls, usage dashboards, and cost optimization reports. By abstracting infrastructure complexities, TensorBlock accelerates development cycles and ensures reproducible, production-ready AI solutions.