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RAG on Prem

Run EyeLevel's RAG platform, GroundX, wherever your data lives: air-gapped, on-premises, hybrid cloud and managed cloud

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The World's Most Accurate RAG Now Runs in the Most Secure Data Center... Yours

RAG (retrieval augmented generation) is revolutionizing LLM-powered applications with private data integration. But first-generation RAG tools fall short for enterprise needs. They lack accuracy, scalability, and security. They can't autoscale for growing workloads or run in the world's most secure data centers, including on-premises installations. Until now...

Built on Kubernetes and Open Source Models
GroundX is the world's only RAG platform built on Kubernetes and fine-tune open source models. That means you can effortlessly run it, scale it and secure it in your data center.
Air-Gapped On Premises
Capable of running fully offline in its own namespace, GroundX integrates CPU and GPU pods for high-performance AI-driven workloads, supported by MySQL, Redis, OpenSearch, Kafka, and MinIO.
Scalable
GroundX autoscales to any workload, doesn't suffer typical accuracy degradation of vector systems at scale and outperformed Pinecone for accuracy in a head-to-head study.
Easy to Deploy
Easily deploy GroundX on your Kubernetes cluster with our Helm operator and get version control, easy roll backs and full control of your RAG deployment.
Architecture
Under the hood, GroundX dynamically allocates 18 CPU pods for managing search queries and document processing workloads. It also includes 2 GPU pods running fine-tuned models for document analysis, alongside 1 GPU pod dedicated to search relevance scoring.

This architecture is designed to scale with demand, using Kubernetes autoscaling for efficient resource usage. Whether processing documents or delivering accurate search results, the system ensures high performance, reliability, and ease of deployment for Kubernetes DevOps teams managing offline environments.

GroundX Ingest Architecture

GroundX Search Architecture

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