Jumpstart AI on IBM Power: The Wallaroo AI Starter Kit
Wallaroo.AI empowers your team to leverage familiar tools while integrating cutting-edge AI technologies. Our strategic partnerships and robust integrations enable you to maximize resources, enhance productivity, and accelerate AI innovation.
Leveraging top technologies to streamline your AI workflows and accelerate time to value.
AWS serves as a cloud platform for deploying and running AI models in production, ensuring scalability and reliability.
Apache Arrow, an open source project providing a common data format for analytics workloads, enhances inference speed and accuracy using table inputs.
Arm's chip technology is used for deploying and running AI models, particularly at the edge, delivering high performance and efficiency.
Integration with AzureML enhances its capabilities for seamless AI model serving and deployment.
Integration with Databricks optimizes AI model serving, making the deployment process smoother and more efficient.
Google Cloud Platform supports the deployment and running of AI models in production, offering a robust and scalable cloud environment.
Integration with Grafana Labs provides advanced querying, visualization, and alerting on metrics, enhancing monitoring capabilities.
Helm, a package manager, simplifies the installation, upgrade, and management of applications on Kubernetes clusters.
Tools from Hugging Face facilitate faster model training and deployment for natural language processing tasks.
IBM Cloud supports the deployment and running of AI models, offering enterprise-grade scalability and security.
Jupyter Notebooks are used for experimentation and visualization, streamlining the model development process.
MLflow, an open source platform, manages the end-to-end AI lifecycle, ensuring seamless model management.
Nvidia hardware powers high-performance AI workloads in various applications using their GPUs.
ONNX standard facilitates model conversion and interoperability between different deep learning frameworks and hardware platforms.
Part of the Open Grid Alliance, focused on developing edge AI applications by integrating compute, data, and intelligence for context-aware solutions.
Pandas, a Python library for data analysis and manipulation, enables efficient data handling and processing.
Python, a versatile programming language, is used for developing and deploying AI models efficiently across various applications.
PyTorch, a deep learning library, is used for developing and training neural network-based models, facilitating advanced AI solutions.
Integration with scikit-learn enhances AI capabilities by developing and training predictive models on structured data.
Tableau, a data visualization tool, analyzes and presents business intelligence insights within the AI lifecycle.
Tableau, a data visualization tool, analyzes and presents business intelligence insights within the AI lifecycle.
XGBoost, a powerful library, is used for developing and training high-performance predictive models on structured data.
Unblock your AI team with the easiest, fastest, and most flexible way to deploy AI without complexity or compromise.
