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DeReticular’s RIOS Campus: An AI-Powered Engine for Rural and Post-Conflict Revitalization

November 1, 2025 by Michael Noel


DeReticular’s RIOS Campus: An AI-Powered Engine for Rural and Post-Conflict Revitalization

DeReticular, an artificial intelligence-focused research and innovation firm, is pioneering a new approach to infrastructure development with its groundbreaking Rural Infrastructure Operating System (RIOS). At the heart of this initiative is the RIOS Campus product line, a series of integrated, self-sustaining systems designed to bring digital and physical infrastructure to underserved areas, particularly in rural and post-conflict zones. The RIOS Campus is not merely a collection of hardware; it’s an AI-native economic engine engineered to be self-funding, resilient, and transformative for the communities it serves.

The RIOS Campus Product Line: A Comprehensive Overview

The RIOS Campus product line is offered in two main configurations: the RIOS 15 Campus and the more robust RIOS 30 Campus. Both are built around a central Core Compute Cluster, the revenue-generating heart of the system.

Brand: DeReticular

Product Details:

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Specifications:

The RIOS Campus is a modular and scalable system that integrates several key technologies:

  • Core Compute Cluster (RIOS-CC-1000): The foundational element of the RIOS Campus is a high-performance compute cluster. In the case of the RIOS 30 Campus, this is the $1.25 million RIOS-CC-1000, a certified RevoFi Trusted Compute Cluster. This cluster is designed to handle high-demand global AI workloads, including machine learning, data rendering, and decentralized finance applications.
  • Connectivity: The official connectivity layer is provided by Trifi Wireless, utilizing their patented vSIM technology. This ensures a resilient, multi-carrier communication network, delivering reliable, high-speed internet access crucial for the AI-driven platform.
  • Power Generation: Energy sovereignty is achieved through a partnership with Agra Dot Energy. Their Micro Gas-to-Liquid (GTL) conversion technology transforms local waste streams, such as agricultural biomass, into renewable fuel. This powers the AI Compute Cluster and other critical infrastructure, eliminating reliance on unstable or nonexistent power grids.
  • Logistics and Data Collection: The system integrates with logistics networks like Kurb Kars, whose vehicle fleets act as mobile data sensors. This real-world data on road conditions, logistics, and service demand is fed back into the RIOS AI to optimize resource allocation and improve services.

Where It Is Best Deployed:

The RIOS Campus is specifically designed for deployment in areas that have been traditionally underserved by conventional infrastructure models. This includes:

  • Rural Communities: Areas with low population density where traditional infrastructure investment is often not economically viable.
  • Post-Conflict Zones: Regions needing to rapidly rebuild and establish resilient economic and social systems.
  • Developing Nations: Locations seeking to leapfrog traditional infrastructure development stages with a more sustainable and economically independent model.

A prime example of a target deployment is Thayer, Missouri, where a RIOS 30 Campus is envisioned to transform the local economy.

What Kind of Performance Metrics Should You Expect:

While specific quantitative performance metrics are not publicly detailed, the expected outcomes of a RIOS Campus deployment are significant and transformative:

  • Economic Self-Sufficiency: The core principle is the “Data Flywheel Effect.” The AI Compute Cluster generates revenue by selling compute services to the global market. This revenue is then used to fund the initial infrastructure build-out and sustain its ongoing operation.
  • Job Creation: The establishment and operation of a RIOS Campus are expected to create high-tech and clean-energy jobs within the community.
  • Improved Public Services: The integrated logistics and connectivity network can dramatically improve essential services like Non-Emergency Medical Transportation (NEMT), as demonstrated by the planned use of Kurb Kars in the Thayer project.
  • Increased Resilience: By decentralizing critical functions like power and communication, the RIOS system is designed to avoid single points of failure, making communities more resilient to disruptions.

What the Cost Is:

The initial investment for a RIOS Campus is substantial, with the Core Compute Cluster for a RIOS 30 Campus, the RIOS-CC-1000, costing $1.25 million. However, the system is designed to be self-funding, with the revenue generated by the compute cluster offsetting the initial capital expenditure and ongoing operational costs.

What the Big Benefit of Ownership Is:

The primary benefit of owning and operating a RIOS Campus is the achievement of economic and infrastructure sovereignty. Instead of relying on external subsidies or traditional investment models that often extract value from rural communities, the RIOS model empowers communities to own their infrastructure and generate their own revenue. This creates a sustainable cycle of development, where the infrastructure itself becomes an asset-generating enterprise. For a community, this means long-term economic stability, improved services, and a direct stake in their technological and economic future.

The Brand’s Differential Advantage:

DeReticular’s differential advantage lies in its holistic and self-funding approach to infrastructure development. Unlike traditional providers who focus on single aspects like internet connectivity or power generation, DeReticular has created an integrated “operating system” that combines these elements with a revenue-generating AI core. This innovative business model, the “Data Flywheel Effect,” directly addresses the economic challenges that have historically left rural and post-conflict areas behind. The founder, Michael Noel, and his vision of an AI-native economic engine position DeReticular not just as a technology provider, but as a partner in building resilient and autonomous economies.

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