The World's First Neural AI Memory that Functions Like a Human Brain.

Explore Cyrock.ai
Available from Sept. 2026

• Access to petabyte AI knowledge in near real-time
• Reduces compute, energy & infrastructure costs by ~80%
• Unifies graph, vector & full-text search in a single, native solution
• Engineered for RAG/GraphRAG within a sovereign enterprise AI
• For Cloud, On-Prem & Edge deployments

Today‘s Vector & Graph Databases Used for GenAI:

Why the Traditional Server DB Architecture Wastes Up to 80% Compute, Energy & IT Budgets, and Breaks at Petabyte-Scale.

All today's vector & graph databases used in Enterprise AI stacks are based on the traditional server database architecture, which has been a great success for previous classic use-cases, but breaks beyond 10 TB AI Knowledge.
The Intelligence Wall

The ideal AI Knowledge is strongly connected, dynamic, and infinitely growing. However, server databases cannot scale with infinite AI Knowledge due to their monolithic, static architecture and the strong coupling between data volume and RAM and computing power.

Static, Monolithic Architecture
The RAM-Cost-Wall
The Serverless Illusion
Monolithic Database Server
Cyrock.AI Neural Cell Architecture – Inspired by Serverless Functions.

Cyrock.AI: Revolutionary Data Storage Cell Architecture.

01
From Monoliths to Microservices: A Proven Success.
For over a decade, software vendors and leading enterprises have invested heavily to abandon 24/7 monoliths in favor of serverless microservices that can scale to zero. Serverless architectures have demonstrated up to 85-90% reduction in idle compute cost (AWS Lambda case studies). This architectural shift aims to align infrastructure costs perfectly with actual demand - eliminating the massive financial waste of idle infrastructure.

Cyrock.AI applies the same architectural principle and transformation to state management, storage, and retrieval.
Microservices-Principle
02
Transforming the Monolithic Database Server to a Network of Micro Data Storage Cells.
With the rise of microservices, other key infrastructure software components have already undergone a radical transformation: the good old Java application server, like WebLogic or JBoss. Instead of a single monolithic Java application server, every individual microservice now possesses its own kind of Java micro application server, such as Quarkus.

We have now implemented this transformation on the monolithic database server architecture and have replaced it with a micro data storage cell, each consuming only ~0.001 CPU, ~100+ MB RAM, to be executed within thousands of tiny data storage services.

When the app requests data, a new cell is invoked in milliseconds, retrieves data from the storage layer, returns it to the app, and shuts down. Hot data is cached, thus cells can be both stateless or stateful. CPU power and RAM are only allocated to active cells. No compute, no costs.
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03
Most Complex Knowledge Graphs Distributed & Infinitely Scalable on Kubernetes
Cyrock.AI is designed to span even the most complex knowledge graphs across Kubernetes clusters and scale elastically with high efficiency through the Cyrock.AI Cell architecture. Each subgraph is associated with a serverless data cell that loads the subgraph only on demand.

This enables traversing through gigantic graphs while minimizing CPU and RAM consumption. High-efficiency GraphRAG at scale.
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04
Petabyte-Scalable On Kubernetes.
The Cyrock.AI cell architecture runs on Kubernetes. The system treats the underlying infrastructure as a fluid resource rather than a rigid box. It turns data storage into a utility that grows exactly as your business grows, ensuring you never hit a performance or cost wall.
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05
Cyrock.AI: Stateful AI Knowledge Frabric
Cyrock.AI is a unified AI memory layer natively combining vector search, graph search, fulltext search, and caching on a truly serverless cell infrastrucutre infinitely scalable on Kubernetes.
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06
80% TCO Reduction of Compute, Energy, Carbon Emissions & Infrastructure Costs.
The Cyrock.AI cell architecture runs on Kubernetes. The system treats the underlying infrastructure as a fluid resource rather than a rigid box. It turns data storage into a utility that grows exactly as your business grows, ensuring you never hit a performance or cost wall.

Want to find out how much you wil save?
Let's start with a POC.
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cell-architecture

From Monoliths to Microservices: A Proven Success.

For over a decade, leading enterprises and middleware providers have invested millions to abandon bloated 24/7 monoliths in favor of serverless microservices to eliminate the massive financial waste of idle infrastructure. By replacing always-on servers with event-driven execution that scales to zero, this architectural shift ensures you stop paying for unutilized capacity and align infrastructure costs perfectly with actual demand. Continuing to run monolithic systems in a cloud-native and AI era is choosing to burn compute, energy, and capital.
cell-architecture

Transforming the Monolithic DB Server to a Network of Micro Data Storage Cells.

We have replaced the monolithic database server with a network of tiny, isolated micro data storage cells that can elastically scale up depending on the workload and scale down to zero when the load decreases.
Only when the app requests data, a new cell is available in microseconds, retrieves data from disk, returns it to the app, and shuts down. Cells can also cache data and become stateful. CPU power and RAM is only allocated to active cells. No CPU power, no costs.
cell-architecture-on-kubernetes

Highly Scalable through Kubernetes.

Cyrock.AI's cell architecture runs on Kubernetes. Thus, Cyrock.AI treats the underlying infrastructure as a fluid resource rather than a rigid box. It turns data storage into a utility that grows exactly as your business grows, ensuring you never hit a performance wall.
80percent

80% TCO Reduction of Compute, Energy, Carbon Emissions & Infrastructure Costs.

Cyrock.AI's Cell Architecture ensures that the system only consumes computing power for data that are actually in use, while unused system regions are automatically shut down. This enables savings of up to 80% in CPU power, energy, carbon emissions, and infrastructure costs.
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Distributing & Highly Scaling Complex Graphs on Kubernetes.

Cyrock.AI is built to highly efficiently store, distribute, and scale any complex graph structure through Kubernetes, and to reload and restore completely or partially in RAM on-demand. Based on native Java object graphs, Cyrock.AI can handle any data types, structured and unstructured data, collections, vectors, and metadata.
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Cyrock.AI: Long-Term Memory for GenAI

A data storage cell is tiny, starts in milliseconds, fetches data from the storage, returns data to your app and shuts down. No CPU resources, no costs.
Get Started
Choose Your Cyrock.AI Component:

Cyrock.AI
Technology Stack

For the highest demands on large enterprise GenAI workloads:

Cyrock.AI Knowledge Fabric

The world’s first cell-based, petabyte-scale AI Knowledge Fabric designed for the most demanding enterprise AI workloads.
Cell Architecture
On-Demand cells scale dynamically with your workload, slashing idle compute costs to near-zero.
Multi-Model Support
Seamlessly unify high-speed Vector Search, complex GraphRAG, and structured business logic within a single
Scale to Near-Zero
Unlimited horizontal scalability and near-zero latency for massive datasets, ensuring you never hit a performance ceiling.
Sovereign by Design
Built for total isolation. Your data and your LLM interactions never leave your infrastructure, ensuring 100% compliance and IP protection.
Enterprise Resilience
Designed for mission-critical AI workloads with built-in high availability and seamless integration into the Kubernetes ecosystem.
Cyrock-AI-Knowledge-Fabric
Plug-and-Play RAG/GraphRAG System:

Cyrock.AI GRAPH-RAG

A complete system for the rapid and simple installation and configuration of a full RAG/GraphRAG system based on the Cyrock.AI Knowledge Fabric. Built for companies that want to independently set up and operate their own sovereign enterprise AI on-prem or in a private cloud environment.
Cyrock-AI-GraphRAG
Embedded Java Graph and Vector Search Engine:

Cyrock.AI Embedded

The foundational, open-source engine of the Cyrock.AI ecosystem, designed for developers who need a high-performance graph and vector database running directly within single-node Java applications. Pure-Java. No more external APIs, vector and graph databases required.
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Next Generation Caching & In-Memory Data Processing:

Cyrock.AI Cache

A high-performance distributed AI caching platform that allows caching and searching of massive datasets. Up to 60-90% RAM and infrastructure cost reduction compared to traditional cache solutions through built-in persistence, disk-swapping, and intelligent lazy-loading without sacrificing millisecond-level access.
Cyrock-AI-Cache
Database to Vector-Store Synchronization:

Cyrock.AI DB-Sync

A data integration platform that monitors your traditional databases and automatically updates your vector stores, ensuring your AI models always have access to the most current enterprise data. Database-independent.
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