Pliops & Zilliz Team Up to Slash Costs for Large-Scale AI Applications

NEW YORK, NY – November 17, 2025 – Pliops and Zilliz today announced a strategic collaboration aimed at significantly reducing the cost and complexity of deploying large-scale Retrieval-Augmented Generation (RAG) applications. The partnership combines Pliops’ LightningAI hardware acceleration platform with Zilliz’s Milvus open-source vector database, offering a solution designed to make advanced AI capabilities accessible to a broader range of businesses.

Addressing the AI Infrastructure Bottleneck

The rapid growth of generative AI is creating unprecedented demand for computing infrastructure. While large language models (LLMs) have captured public attention, the underlying infrastructure required to support them—particularly the ability to efficiently store, search, and retrieve vast amounts of data—remains a significant challenge. RAG, which enhances LLMs with external knowledge, is becoming increasingly popular, but scaling vector databases to handle billions of vectors efficiently and affordably has proven difficult. “The cost of infrastructure is consistently cited as a major impediment to the broader adoption of generative AI,” said one industry analyst. “Companies are eager to leverage these technologies, but they need solutions that fit within their budgets.”

Pliops and Zilliz are betting that their combined solution can fill that gap. Pliops’ LightningAI platform leverages specialized hardware—Extreme Data Processors (XDP)—to accelerate data processing, offloading tasks from CPUs and GPUs and reducing bottlenecks. Zilliz’s Milvus, an open-source vector database built for performance and scalability, provides the storage and search capabilities needed to support RAG applications. By combining these technologies, the companies aim to deliver a solution that offers both performance and cost efficiency. “We’re seeing tremendous demand for solutions that can handle the scale of data required for modern AI applications,” explained a source familiar with the partnership. “This collaboration is a direct response to that demand.”

Technical Innovations Drive Scalability and Efficiency

The key to the partnership’s success lies in the technical innovations underlying both platforms. Pliops’ XDPs are designed to handle data-intensive tasks like compression, deduplication, and encryption at wire speed, freeing up host resources and improving overall performance. “The architecture allows for significant improvements in data throughput and reduced latency,” explained another industry source. “This is particularly important for RAG applications, where fast retrieval of relevant information is critical.”

Zilliz’s Milvus, built on a cloud-native, microservices-based architecture, is designed for scalability and flexibility. Its separation of storage and computation allows for independent scaling of each layer, enabling it to handle billions of vectors efficiently. The latest enhancements to Milvus, including multi-tier storage and a key-value abstraction layer, further optimize performance and cost efficiency. “Multi-tier storage allows us to store frequently accessed data in fast, but more expensive storage, while less-accessed data can be stored on cheaper storage,” said a Zilliz representative. “This allows us to optimize costs without sacrificing performance.”

A Broader Trend Towards Specialized AI Hardware

The partnership between Pliops and Zilliz is emblematic of a broader trend towards specialized AI hardware. While general-purpose GPUs have long been the workhorse of AI, many companies are now turning to custom silicon to address the specific needs of different workloads. “We’re seeing a shift from one-size-fits-all hardware to more specialized solutions,” noted a technology analyst. “Custom silicon can deliver significant performance and efficiency gains for specific applications.”

This trend is being fueled by several factors, including the increasing complexity of AI models, the growing demand for edge computing, and the desire to reduce energy consumption. “AI workloads are becoming increasingly demanding,” said one source. “General-purpose hardware is often not enough to meet these demands.” By combining specialized hardware with optimized software, companies like Pliops and Zilliz are positioning themselves to capitalize on this growing market. The collaboration highlights the growing importance of co-design—optimizing both hardware and software to deliver the best possible performance and efficiency. “It’s not enough to just have fast hardware,” explained another industry expert. “You need software that can take full advantage of that hardware.” The combination of Pliops’ LightningAI platform and Zilliz’s Milvus vector database represents a significant step towards that goal.

The companies showcased their integrated solution at Supercomputing 2025, demonstrating the potential of their combined technologies to address the challenges of large-scale RAG deployments. “The response from attendees was overwhelmingly positive,” said a Pliops representative. “We’re confident that this partnership will help unlock the full potential of generative AI for a wider range of businesses.”