Modular colocation, server systems, private cloud, cyber security and applications. Five offerings on one sovereign stack. Pick what solves your problem. Own more as your demand grows.
Domain agents, vertical apps, and MCP-style skills running on your infrastructure, such as citizen services, CBDC, defence copilots, finance assistants, and healthcare AI.
PQC + QKD defence-in-depth, sovereign HSMs, and crypto-agility that protect workloads with sensitivity lifecycles measured in decades.
Bare-metal, VMs, GPU pools, QPU queues, and object/block/file storage, all in-country and addressable from a single white-label control plane.
Three steel modules, twenty 20 kW racks, dual UPS, and in-row DX cooling, all witness-tested before shipping. Capacity lands when the trailer arrives.
A complete 400 kW Tier III data centre packaged into three insulated steel modules. Twenty 20 kW racks, dual UPS, eighteen in-row cooling units, hot-aisle containment, integrated fire detection and suppression, all assembled, witness-tested, and commissioned at the factory before being trucked to site. Civil works run in parallel; capacity lands when the trailer arrives.
Three insulated steel enclosures combine into one Tier III data centre: two IT rooms hosting twenty 20 kW racks plus a dedicated power-and-cooling room. Witness-tested at the factory before shipping.
An EIA-310-D cabinet with 70% perforated front and split rear doors that open 130° for service. Tool-less doors, removable power trough, and a removable bottom cover for raised-floor cabling. Frame rated to 1,420 kg, IP20.
A real-time platform spanning every rack and site: live PUE and energy analytics, rack-level asset and capacity views, ITIL-aligned incident and work-order flow, plus a mobile inspection app with QR-coded assets.
Every Tier III pod arrives commissioned and factory-tested. These are the systems wired up when the trailer lands.
Two 1,600 A main distribution boards with automatic transfer, two 500 kVA UPS systems, and vertical PDUs. Every rack gets independent A and B feeds.
Eighteen in-row DX units with paired outdoor condensers, hot-aisle containment, and a dedicated electrical-room split. Validated against Nairobi's 20-year ASHRAE profile at 400 kW.
Multiple terrestrial and submarine carriers terminating into a meet-me room. Cross-connects on request, no lock-in.
Modules are wired, plumbed, and commissioned off-site, then witness-tested. Civil works run in parallel; capacity lands when the trailer arrives.
Insulated 80 mm steel panels, 60-minute fire rating, EI60-rated doors, integrated detection, and clean-agent suppression. Aspirating smoke detection optional.
PoE-managed access control on EI60 doors, full IP CCTV with NVR, and a managed PoE switch. Wired, mounted, and configured at the factory.
Sites placed where energy, fibre, and regulatory clarity converge. Operated by local teams under local jurisdiction, monitored from your DCIM.
Performance verified at Nairobi altitude across the full annual temperature band. Efficiency holds where most reference designs degrade.
A complete Tier III megawatt at a fraction of a ground-up build's cost. Time-to-deploy compressed from 18-36 months to about six. Every decision sized for compute per watt and per dollar.
Our flagship deployment sits inside the Hell's Gate deep tech park, powered by Kenyan geothermal. It is the clearest picture of what modular colocation looks like on the ground.
Every Navon server is designed to the job it runs, with each watt of the 20 kW envelope spent on compute, or each rack unit spent on capacity, sized to what the customer actually runs. The same engineering produces five turnkey reference configurations that cover the most common sovereign-compute use cases. Four are compute-led and one is storage-led, all shipping pre-integrated, cabled, witness-tested, and commissioned.
A single 20 kW rack pre-built for university, lab and research workloads: three CPU nodes for general compute, two 8-GPU training nodes, and a half-petabyte NAS, on a redundant 25 / 100 G fabric. Fourteen rack units left free for the team to grow into.
Five 20 kW racks built around 8-GPU training systems, each paired with a Blackwell-class PCIe accelerator node to fully utilise the 20 kW envelope. Engineered for large-model training and high-throughput inference, with a flat 400 G fabric across the cluster. Ships pre-integrated with vLLM, Ollama, and an OpenAI-compatible endpoint, the same serving stack as the sovereign cloud, on dedicated silicon. Two tiers: latest-generation or prior-generation HGX.
Five 20 kW racks built around dense PCIe inference nodes, tuned for serving traffic rather than training runs. Memory-bandwidth-rich silicon, packed as tightly as the 20 kW envelope allows, behind a vLLM-class serving stack with continuous batching and paged-KV-cache. Optimised for the metric that actually shows up on the bill: cost per million tokens out, not peak FP16 TFLOPS.
Five 20 kW racks built around a non-mainstream AI accelerator paired with general-purpose PCIe compute. For customers who want serious training and inference capacity without committing the entire stack to a single silicon supplier, giving sovereignty and supply-chain diversity by design.
Storage-led racks shaped to whatever the customer actually holds, from a few hundred terabytes for a research lab to multiple petabytes per rack for sovereign archives, scientific data lakes, and long-tail data residency. Mostly disk shelves, a slim controller, and the same dual-corded power and 25 / 100 G fabric the compute racks ride on. Configurations span all-flash for low-latency archive, hybrid NVMe + HDD, and pure HDD for true cold tiers.
We engineer infrastructure backwards from the application, not from the catalogue, to match each workload and its environment. That means optimal performance, cost-efficiency, and seamless integration with the modular Tier III data centre that hosts it.
Configurations are selected by end-use case, such as AI inference, HPC analytics, training, and storage. The most suitable hardware system is determined by the use case's performance requirements and cost constraints, not by what's on a SKU sheet.
Vertical and horizontal scaling paths to track software evolution, with margins of safety so customers never top off on compute. Cooling, IT-load and space envelopes are sized after the application is locked, not before.
Competitive CapEx operationalised through energy-aware configurations and PUE-tuned designs. A modular growth model, where capacity follows demand rather than the other way around, keeps every euro and every watt working.
Encrypted storage, tamper-evident racks, in-jurisdiction compute. High availability and extended warranties are included by default, never retrofitted at the contract stage.
Every dial sized to the workload, not the catalogue. Every rack lands in a Navon module.
Compute racks sized so steady-state load lands ≈95% of the 20 kW envelope. Storage racks sized to what the customer actually holds. CapEx on what gets used, not stranded.
Every node dual-corded across A and B PDUs, sized so single-feed failover carries the full ≈19 kW load within budget.
Cluster-wide Ethernet: 25/100 G for research and inference, full 400 G for training and open-accelerator clusters. Vendor-open switch stack, no network silo.
Crating, freight, on-site rack-and-stack, network and software bring-up. A specialist field team. Customer takes delivery of a working cluster, not a parts list.
Every configuration sized to the same 20 kW rack envelope as the 400 kW MDC. Compute and storage live side-by-side under the same facility, DCIM, and cooling budget.
Where the workload demands the latest GPU silicon, we ship it. Where you'd rather hedge supply-chain or sovereignty risk, we offer a credible non-mainstream accelerator path on the same rack, fabric, and operating model.
The research-rack reference design has three CPU nodes, two 8-GPU training nodes, a half-petabyte NAS, a dual leaf fabric, and dual-corded power. Click any unit to inspect its hardware, networking, and load.
Two GPU nodes for training and high-throughput inference. Three CPU nodes for general compute and orchestration. One NAS for shared training data and checkpoints. Two leaf switches and two PDUs in active/active redundancy. Hover any rack unit to highlight its connection.
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| Device | PSU config | Feed A draw | Feed B draw | Total | Notes |
|---|---|---|---|---|---|
| GPU Node 1 | 2× 3 kW redundant | 3.25 kW | 3.25 kW | 6.50 kW | Active/active across A+B |
| GPU Node 2 | 2× 3 kW redundant | 3.25 kW | 3.25 kW | 6.50 kW | Active/active across A+B |
| CPU Node 1 | 2× 1.6 kW redundant | 0.75 kW | 0.75 kW | 1.50 kW | Active/active across A+B |
| CPU Node 2 | 2× 1.6 kW redundant | 0.75 kW | 0.75 kW | 1.50 kW | Active/active across A+B |
| CPU Node 3 | 2× 1.6 kW redundant | 0.75 kW | 0.75 kW | 1.50 kW | Active/active across A+B |
| NAS | 2× 1.6 kW redundant | 0.50 kW | 0.50 kW | 1.00 kW | Active/active across A+B |
| Asterfusion leaves | 2× PSU per switch | 0.28 kW | 0.27 kW | 0.55 kW | Primary on A, redundant on B |
| Feed totals | 9.53 kW | 9.52 kW | 19.05 kW | Failover load per feed: ≈ 19 kW (within 20 kW budget) |
Load figures are steady-state estimates derived from component TDPs (EPYC 9965 ≈ 500 W; RTX 5090 ≈ 575 W TGP) plus platform overhead. Peak training bursts can push GPU nodes ≈ 10-15% higher, so size PDUs and breakers for peak, not average. On single-feed failover the surviving feed carries the full ≈19 kW, so both PDUs are sized to 20 kW.
A complete sovereign cloud stack: bare metal and virtual machines for general-purpose CPU workloads, multi-tenant GPU pooling for AI training and inference, sandboxed access to partner quantum hardware, and object, block and filesystem storage, all under one API and all in your jurisdiction. Built on best-of-breed open source where it adds leverage, white-labelled where it pays.
You don't have to rent your infrastructure from a hyperscaler in another jurisdiction. This short film shows how Navon lets you stand up your own sovereign private cloud, with CPU, GPU, QPU, and storage under one control plane, in your own country, and with the performance and economics to compete head-on with the global clouds.
Bare metal servers, virtual machines, managed Kubernetes, and managed databases for everything that isn't AI training. Provision in minutes through a single API; private VPCs, firewalls, and cross-cloud gateways for hybrid workloads. The right answer for web services, data platforms, internal tooling, and the long tail of compute that doesn't need a GPU.
Software-defined GPU pooling layered on Navon's bare metal, where overcommit-aware scheduling pushes utilisation toward 100%, with VRAM and TFLOPS provisioned in real time. Rebrandable self-service portal, consumption billing per tenant, and a one-click model library. White-labelled on the hosted.ai GPU cloud platform.
Production model serving on owned GPU pools, using vLLM, TGI, and TensorRT-LLM for high-throughput workloads, and Ollama-ready for self-hosted open weights. An OpenAI-compatible endpoint sits in front, so SDKs and tools you've already integrated, such as LangChain, LiteLLM, OpenRouter, LlamaIndex, and Cursor, work without code changes. You bring your stack and we provide what's underneath.
Sandboxed access to curated partner quantum hardware via a queue API, covering algorithm development, benchmarking, and hybrid HPC + QPU pipelines, all under Navon's sovereignty posture. For research teams, defence labs, and government programmes building toward post-classical workloads alongside their classical compute.
NVMe-backed object, block, and filesystem storage tiered to match the workload, with fast media for live data, hybrid for working sets, and cold HDD for archive and compliance retention. S3-compatible API for object, POSIX for filesystem, iSCSI for block. All in the customer's jurisdiction by default, with cross-region replication only on explicit request.
Cloud customers who can size their floor, such as production inference, recurring training jobs, and working-set storage, pre-commit a 1-year or 3-year horizon and land closer to colocation economics than to public cloud, without leaving the jurisdiction.
Indicative anchors · normalised to a $1,000/mo baseline · final pricing confirmed at contract
The big three (AWS, Azure, GCP) run proprietary stacks top-to-bottom. There's a parallel universe of open-source projects that, composed correctly, replicate most of what a hyperscaler does, already in production at OVHcloud, CERN, Walmart and dozens of telcos. We've assembled the full stack, layer by layer, and engineered around the gaps the open ecosystem leaves behind.
Pure open source has known gaps, such as billing & invoicing, marketplace & service catalogue, global traffic management, managed-database wrappers, and SLA & support tooling. These are where most open-stack projects die. Our white-label control plane closes them, so customers get the cost-curve and sovereignty of open source and the polish of a commercial cloud.
On top of the seven-layer base, three upstream OSS projects sit inside the GPU layer where they matter most: distributed inference, memory optimisation, and AMD-tuned kernels. Credit and links to upstream below.
A decentralised LLM inference engine that splits transformer blocks across heterogeneous peers. Workers run with as little as 4 GB VRAM, so models that don't fit any single node still run cleanly across the cluster. This is useful for very large open-weight models on mixed silicon.
SVD-compressed inference for memory-bandwidth-bound workloads, with a demonstrated ≈1.45× end-to-end speedup on Llama-class models with logit-matched accuracy. Useful where serving cost is gated by memory throughput rather than raw FLOPs.
Optimised distributed kernels for 8× AMD MI300X: All-to-All for MoE, GEMM-ReduceScatter for tensor parallelism, and AllGather-GEMM for distributed inference. Where customers run AMD silicon for inference, we ship these for the throughput uplift.
Whichever silicon, whichever region: same control plane, same sovereignty model, same self-service shape.
Every CPU, GPU, QPU job and storage object lives within the customer's jurisdiction. Cross-border replication only on explicit contract, never by default.
Bare metal, VMs, GPU pools, QPU queues, and storage tiers all addressable through the same REST API and self-service portal. No console-switching to switch silicon.
Take the platform under your brand. Telcos, ministries, and DFIs run sovereign clouds with their colours, pricing, and tenants. The hosted.ai layer rebrands end-to-end.
Every operator action exposed through REST, with Terraform providers and Ansible playbooks for repeatable deployment and Day-2 ops. Automation-first, console-second.
VRAM-hours, TFLOPS, CPU cores, storage GB-month, bandwidth, QPU shots. All metered and billed per tenant, with regional pricing and built-in WHMCS hooks.
30+ GPU SKUs across both major vendors, alternative non-mainstream accelerators, and curated partner QPU hardware. One control plane. No silicon lock-in.
Security that you don't control is just rented trust, and sovereignty that isn't quantum-protected has an expiration date. Navon brings the two together into a single deployable platform that covers the modular shell, the power, and the cryptographic layer, all under the customer's flag and all engineered to outlast the post-quantum transition.
Quantum computers will break the encryption protecting today's applications, and adversaries are already harvesting data to decrypt later. This short film shows how Navon's hybrid post-quantum cryptography future-proofs your apps now, delivered with the price-performance to make quantum-safe security the default, not a premium.
Data security gives the cryptographic foundation. Data sovereignty gives the physical and legal control. Quantum protection makes both durable across the post-quantum transition.
Hardware-native protection, not a software overlay. Tamper-resistant key vaults, physics-based entropy, and an agility engine that re-encrypts the estate as standards move.
Sovereignty is a physical condition, not a contractual assurance. Customers own the shell, the power, the network perimeter, and the keys, across National Vaults, cross-border Data Embassies, and air-gapped pods.
Quantum protection is not a 2030 retrofit. It is built in. Classical and PQC algorithms run in parallel today, with QKD reserved for the highest-assurance links between sovereign nodes.
Physical infrastructure controls digital sovereignty. The organisations that own the shell, the power, and the cryptographic layer own the trust.
Quantum security is not one technology. It is a layered defence. Physics-based key exchange and software-defined post-quantum cryptography address different threat vectors at different points in the stack. Together they cover both current and future quantum threats.
Live at Hell's Gate Deep Tech Park. Hardware-level QKD and software-defined PQC run side by side in a single, integrated environment, open to governments, telcos, banks, and research partners for evaluation, validation, and deployment of quantum-secure systems on commercially proven gear.
Built with ID Quantique (Geneva, a global leader in QKD, deployed in Korea, Singapore, EU) and ExeQuantum (an ISO 27001 certified PQC stack covering discovery, encryption, and sovereign architecture).
Citizen registries, treaty archives, and central-bank infrastructure carry sensitivity lifecycles measured in decades. They are the first to demand quantum-resilient sovereignty, and the largest beneficiaries of getting it right early.
Quantum-resilient citizen registries, digital embassies, classified research, and national cryptographic inventories ahead of mandate.
Encryption upgrades for core banking, quantum-secure transaction APIs, and PQC-mandate readiness ahead of global regulation.
Quantum-secure managed services for enterprise, inter-city QKD links, and backend protection against harvest-now-decrypt-later.
Hardware-rooted resilience for industrial control, IoT communications secured with pre-shared quantum keys, sector-specific compliance.
Lifelong patient records, biometric registries, and identity systems whose sensitivity windows exceed any classical cipher's lifetime.
University collaboration, applied quantum-security research, and a continental sandbox for cybersecurity startups building on real infrastructure.
This is the top of the Navon stack: sovereign AI applications running on your data, in your jurisdiction, on your hardware. Three composable layers: applications solve sector problems, agents orchestrate the work, and skills are the atomic primitives both depend on. It is operable through low-code workflows for business and operations teams, and full SDKs for engineering groups, all on the same platform and the same data through different entry points.
Vertical applications shaped to the workflows of each sector, running on Navon's sovereign cloud, encrypted at rest with PQC, and trained on locally held corpora. Each is a packaged, low-code outcome that domain teams can configure without an engineering rebuild.
Identity, registries, document workflows, and government copilots that keep every byte under national control. Designed for ministries that cannot send citizen data to a foreign cloud.
CBDC issuance, real-time fraud and AML, lending models, and quantum-secure transaction processing, built for central banks, commercial banks, and exchanges with sub-second SLAs.
Patient-record platforms, medical-imaging AI, and clinical-trial assistants, running on data whose sensitivity windows exceed any classical cipher's lifetime.
Sovereign LLMs on classified corpora, encrypted comms, and ISR analytics, deployable in offline quantum pods where no byte ever crosses an external boundary.
Demand and load forecasting, predictive maintenance for turbines and substations, and operations copilots, running close to the SCADA layer for low-latency decisions.
Network-optimisation agents, customer-service automation in local languages, and revenue-assurance models, for operators ready to embed AI in the OSS/BSS stack without offshoring data.
Personalised tutors in local languages, sovereign research compute for universities, and a continental innovation hub, built with academic partners and on-site internship programmes.
Industrial control monitoring, IoT fleet management, and safety-critical anomaly detection, at the edge, on-prem, with quantum-resilient device identity.
Customs and border copilots, supply-chain agents, and port operations AI, designed for the cross-border data flows of regional trade blocs and the harmonisation of customs regimes.
Agents are the workers. They are long-running, tool-using, multi-step reasoners that combine skills to deliver outcomes, and they are the substrate every application above this layer is built on.
Parses, classifies, extracts, and reasons over unstructured documents at scale, such as passports, contracts, medical scans, legal filings, and customs declarations. Outputs JSON, decisions, or downstream actions.
Maps the regulatory landscape, scans transactions and configurations against policy, generates audit-ready reports, and flags violations the moment they appear. Ready for NIST, NDPA, GDPR, and emerging PQC mandates.
Retrieval-augmented research across closed-domain document stores such as internal reports, citizen records, legislation, and scientific literature. Cites sources, supports follow-up reasoning, and never leaks the corpus to a foreign endpoint.
Forecasts, scenario simulation, and structured trade-off analysis on operational data, for executive dashboards, central-bank monetary committees, energy operators, and ministers running national programmes.
Real-time translation and speech across English, French, Arabic, Swahili, Amharic, Yoruba, Hausa and more, with text, voice, and call-centre integration. Tuned for the languages global LLMs underserve.
Long-running, stateful workflows that wire AI into existing systems, covering approvals, escalations, notifications, ticket routing, and downstream API calls. Replaces glue code, RPA, and the spreadsheet-and-email layer.
Skills are the Lego bricks. Every agent is composed of skills, and every application is composed of agents. You build a skill once and reuse it across sectors, swapping implementations as the underlying models improve.
For workloads where classical compute is hitting its ceiling, such as combinatorial optimisation, drug discovery, financial risk, and post-quantum cryptography, Navon ships a quantum-AI development environment alongside the classical stack. You build, benchmark, and deploy hybrid algorithms on the same infrastructure your AI already runs on, with no bespoke research project, no vendor lock-in, and no second pipeline.
Your existing models do feature engineering and shortlist candidate inputs. There's no code rewrite, so you just drop a quantum subroutine where it pays off.
Optimisation, sampling, or quantum-enhanced learning runs on a real QPU or simulator, selected automatically by the queue based on availability and cost.
Multishot results aggregate into a final answer; the artefact is shipped through the same control plane your classical workloads already use.
Everything needed to build, benchmark, and ship hybrid quantum-classical workloads, from raw hardware access to a smart-contract oracle, on the same sovereign cloud, SDK, and security posture your classical AI already runs on.
Simulators plus real quantum hardware. Build, test, and benchmark on the same machines the next decade of AI will run on.
Seamless quantum-classical orchestration. Mix classical AI inference with quantum subroutines without rewriting your pipeline.
Quantum machine learning, optimisation, and post-quantum cryptography, all production-grade starting points rather than from-scratch research projects.
Sandbox to production on Navon Private Cloud, with the same artefact you trained, the same security posture, and no rewrite at the line.
No-code execution and side-by-side benchmarking across solvers. Multishot aggregation, full result histories, and audit-ready reports.
Simulators, quantum-inspired, ion-trap, superconducting, neutral-atom, and photonic backends are all addressable through one API, with no vendor lock-in.
An encrypted SDK that keeps your data yours. In-country keys, sovereign HSMs, and security baked into the protocol rather than bolted on at the perimeter.
Simple integration via RESTful API plus a built-in Web3 oracle. Wire quantum results into existing IT systems and on-chain workflows.
Skills compose into agents, and agents compose into applications, so when you build a skill once, every sector benefits.
We'll walk you through the workload, the constraint, and the right starting layer, usually a 30-minute conversation rather than a sales process. Or browse the docs first if you'd rather.