Turnkey RAG and OpenAI-Compatible API enable businesses to securely deploy tailored AI solutions with unparalleled cost efficiency and scalability
Vultr, the cloud computing platform, announced a significant expansion to its Vultr Serverless Inference platform, providing organizations with the essential infrastructure needed for agentic AI. Building upon its initial launch earlier this year, these powerful new capabilities empower businesses to autoscale models and leverage Turnkey Retrieval-Augmented Generation (RAG), to deliver model inference across Vultr’s 32 global cloud data center locations.
Agentic AI is predicted to be the next big frontier in AI, with AI agent platforms emerging as dominant leaders in the industry. However, to unlock the full potential of AI agents, organizations need flexible, scalable, high-performance computing resources at the data center edge, closer to the end user. Vultr Serverless Inference emerges as the sole alternative to hyperscalers, offering the freedom to scale custom models with a user’s data sources without lock-in or compromising IP, security, privacy, or data sovereignty.
By leveraging cutting-edge serverless technology accelerated by NVIDIA and AMD GPUs, Vultr automatically scales AI model inference at the data center edge. AI models are served intelligently on the most optimized NVIDIA or AMD hardware available, ensuring peak performance without the hassle of manual configuration. What’s more, Vultr is giving innovators freedom, choice, and flexibility with options to leverage popular open source models including Llama 3. Vultr also enables customers to bring their own model, and deploy their own dedicated inference clusters across any of Vultr’s global data center locations.
“The growing importance of agentic AI calls for developing an open infrastructure stack that addresses the specific needs of enterprises and innovators alike, and Vultr now offers a compelling balance of performance, cost-effectiveness, and energy efficiency,” said Kevin Cochrane, Chief Marketing Officer at Vultr. ”As we expand our Serverless Inference capabilities, we’re offering enterprises and AI agent platforms alike a robust alternative to traditional hyperscalers to effectively deploy and scale agentic AI technologies at the global data center edge.”
With the capability to self-optimize and auto-scale in real-time, coupled with a presence on six continents, Vultr Serverless Inference ensures AI applications deliver consistent, low-latency experiences to users worldwide.
Key features include:
Turnkey RAG: Securely Leverage Proprietary Data for Custom AI Outputs
Vultr’s Turnkey RAG stores private data securely as embeddings in a vector database, allowing large language models (LLMs) to perform inference based on this data.
The result is tailored, accurate AI outputs controlled entirely by the business, ensuring that sensitive information remains secure and compliant with data residency regulations. For organizations looking to implement agentic AI, this enhances the ability of AI systems to deliver accurate, contextually relevant responses in real time. By seamlessly integrating retrieval capabilities with generative models, Turnkey RAG allows AI agents to dynamically access and utilize up-to-date information, significantly improving their decision-making and responsiveness. Turnkey RAG also eliminates the need to send data to publicly trained models, reducing the risk of data misuse while leveraging the power of AI for custom, actionable insights.
OpenAI-compatible API: Improving Cost Efficiency and Scalability
With Vultr’s OpenAI-compatible API, businesses can integrate AI into their operations at a significantly lower cost per token compared to OpenAI’s offerings, making it an attractive option for organizations looking to implement agentic AI. For CIOs managing IT budgets, this cost-efficiency is particularly appealing, especially when considering the extensive potential for AI deployment across various departments. This feature allows CIOs to optimize expenses while leveraging Vultr’s robust infrastructure to scale AI applications globally, eliminating the need for substantial capital investments in hardware or ongoing server maintenance.
Moreover, the OpenAI-compatible API accelerates digital transformation by enabling teams to seamlessly incorporate AI into existing systems. This integration facilitates faster development cycles, more efficient experimentation, and quicker time to market for AI-driven features—all while avoiding the hefty retraining and integration costs typically associated with adopting new technologies. As a result, businesses can harness the full potential of agentic AI more effectively, driving innovation and operational efficiency without straining their resources.
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