Vultr 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.