GenAI Playgrounds

Drive Faster Generative AI Experimentation with GenAI Playgrounds

Provide developers with seamless access to LLMs, while
streamlining the experience of deploying, interacting with, and
managing Generative AI (GenAI) models

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Build enterprise-grade GenAI applications faster and at scale

Provide Curated LLMs for GenAI Development

Provide developers and data scientists with centralized API access to a curated list of enterprise approved, public cloud and self-hosted LLMs for use in their GenAI applications.

Deploy & Operate Self-Hosted LLMs

Allow 1-click deployments of self hosted LLMs such as Llama 3.1, Vicuna, and more from an integrated catalog with support for GPUs and auto scaling infrastructure

Integrated Data Pipelines

Seamlessly connect to internal and external data sources such as databases, cloud storage, and data lake systems. This ensures that the AI models are trained on accurate, up-to-date data, and simplifies the process of preparing datasets for training

Provide Prompt Lifecycle Management

Allow developers to iteratively design and evaluate LLM prompts, maintain history, compare performance and cost across models

Provide Cost Visibility & Governance

Get detailed insights into the costs associated with model usage, allowing teams to track costs down to individual projects, users, and models. This capability enables organizations to monitor and control spending, set budgets, and implement cost-saving measures while ensuring that resources are allocated efficiently

With pre-built models and tools readily available, GenAI playgrounds streamline the AI development process

By providing GenAI playgrounds to developers and data scientists, Rafay customers realize the following benefits:

Accelerated AI Innovation

GenAI playgrounds from Rafay enable rapid experimentation and prototyping, allowing teams to quickly test and refine AI models, driving faster innovation and breakthroughs

Enhanced Creativity and Collaboration

By providing a shared environment for developers and data scientists, Rafay fosters cross-functional collaboration and unlock creative potential, leading to more diverse and innovative AI solutions

Optimized Resource Utilization

Rafay offers cost visibility and governance tools that help track and control model usage expenses, ensuring efficient allocation of resources and maximizing ROI in AI investments

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Scale AI/ML Adoption

Delve into best practices for successfully leveraging Kubernetes and cloud operations to accelerate AI/ML projects.

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Most Recent Blogs

Democratizing GPU Access: How PaaS Self-Service Workflows Transform AI Development

April 11, 2025 / by Gautam Chintapenta

A surprising pattern is emerging in enterprises today: End-users building AI applications have to wait months before they are granted access to multi-million dollar GPU infrastructure. The problem is not a new one. IT processes in… Read More

Rafay and Netris: Partnering to speed up consumption and monetization for GPU Clouds

March 12, 2025 / by Haseeb Budhani

Rafay, a pioneer in delivering platform-as-a-service (PaaS) capabilities for self-service compute consumption, and Netris, a leader in networking Automation, Abstraction, and Multi-tenancy for AI & Cloud operators , are collaborating to help GPU Cloud Providers speed up consumption… Read More

Is Fine-Tuning or Prompt Engineering the Right Approach for AI?

March 6, 2025 / by Rajat Tiwari

While prompt engineering is a quick and cost-effective solution for general tasks, fine-tuning enables superior AI performance on proprietary data. We previously discussed how building a RAG-based chatbot for enterprise data paved the way for creating a… Read More

A couple of hours is all it takes to launch a GPU Cloud