The chat, the agents, the retrieval, the inference. One platform.
A single operating system across HPE, Eviden, Dell, NVIDIA, mixed hardware. Your rack, your choice.
On-prem-first. EU-built. No mandatory cloud calls. Yours to run.
An AI datacenter is not just GPUs in a rack. It is the operating layer that turns compute, storage, and network into an AI service — chat, agents, retrieval, training, observability, multi-tenancy, billing, audit, and a plugin host — all under one configuration grammar. Eldric is that layer. It does not replace your hypervisor, your storage array, your firewall, or your identity provider. It does provide every layer those tools cannot.
Each Eldric module is a named capability with a clear job. Compose the ones you need; skip the ones you don't. They all ship in the same package. They all speak the same configuration grammar. They all upgrade together.
The cluster brain.
Orchestrates the fleet. Pushes topology, distributes the license, handles register and heartbeat, runs the rolling-upgrade orchestrator. See clustering & HA.
Smart load balancing.
Intent classification, AI-aware routing, tool-required substitution. Sends each request to a worker that can actually answer it. How it works.
Models on your hardware.
CPU and CUDA workers. Native GGUF loading without external runtimes. Structured-ML xLSTM workloads alongside the conventional stack. All features.
Storage and retrieval.
File storage with multi-tenant isolation. Vector retrieval. Matrix memory. Replication between data nodes. NFS for shared filesystems. Using RAG.
Agentic reasoning.
Multi-tenant agent runtime. Session memory, query decomposition, multi-agent execution, named workflows. Advanced retrieval.
The public face.
TLS termination, authentication, rate limiting, the embedded chat shell, plugin host. Customers see this; nothing behind it. For developers.
Multi-agent orchestration.
Topologies for fanned-out reasoning: hierarchical, peer-to-peer, ring, star, mesh, hybrid. For deeper agent collaboration than one chat turn permits.
Fine-tuning & federation.
LoRA, QLoRA, DPO, RLHF. Training chains with latent-reasoning techniques. Federated rounds across the worker fleet without moving the data.
A research-data surface.
One registry across 16 categories of scientific sources — astronomy, particle physics, genomics, climate, medical, materials, more. Pluggable.
Messaging & calls.
Email, SMS, WhatsApp, Signal, Teams, XMPP, voice over SIP. A unified message surface; AI-assisted responses with operator approval.
Audio & video.
Speech-to-text, text-to-speech, transcription, voice chat, multimedia retrieval. Local engines and cloud APIs, side by side.
Things & sensors.
Industrial OPC-UA, Modbus, MQTT. Consumer HomeKit, Matter, Netatmo. Predictive maintenance from inference; closed-loop control via structured-ML policy.
Every module exposes a documented API. Every module participates in the same multi-tenant guard. Every module emits OpenTelemetry. The boundary between "platform" and "infrastructure" stays clean: we own the AI surface, you own the metal.
For the operator, this is three jobs the platform makes possible — and one job the platform replaces.
A datacenter that runs Eldric is not a datacenter that runs models. It is a datacenter that runs an AI service — a thing customers buy, with isolation, billing, branding, and operator control. Three jobs the platform makes possible.
Multi-tenant by design. Per-tenant isolation enforced by the kernel — data, sessions, retrieval, and audit all stay inside their own boundary. Per-tenant theming and branding so each customer sees their own product. License tiers built for resale: the operator buys a tier; tenants get a slice.
See the resale model →Any model, any backend. Ollama, vLLM, TGI, NVIDIA Triton, llama.cpp, native GGUF — local. OpenAI, Anthropic, xAI, DeepSeek, Groq — cloud. All under one unified abstraction. Customers ask for a model; the router finds it; the worker serves it. The operator sees one billing surface.
See the backend list →One HQ datacenter and ten branch sites. Vienna and Salzburg. Primary and warm-DR. A peer mesh that gossips state, routes around outages, keeps regional data resident where the customer's contract says it must stay. Cross-WAN, cross-AZ, cross-subnet.
See clustering & HA →The three jobs compose. Sell to enterprises whose data must stay on-prem. Run their inference on the GPUs you already own. Federate the service across the racks you operate — and bill all of it from one place.
Twelve to eighteen months of platform engineering, before the first customer signs up. The pieces a serious AI service needs that nobody actually wants to write from scratch — the substrate beneath the product, the layer that has to be done well or nothing else works. Eldric ships that substrate. Your team builds the product on top.
Build a chat application. Build a research agent. Build a private AI service for your industry. We will not build the application for you — but we will spare you a year of substrate work to get there.
An AI platform that demands a specific vendor's hardware is the wrong shape for the datacenter. Eldric runs on Linux on x86 or ARM, with or without GPUs, on whatever your team already procured. We are not trying to lock you to a chipset, a server vendor, or a network fabric. We are trying to give you a platform that turns those things into an AI service.
A note on Eviden and the European AI-factory posture: BullSequana XH3000 + Smart Management Center is an exceptionally clean fit for the platform — the management plane is Redfish-clean, the supercomputer-class density is real, and the Atos partnership posture aligns with how Eldric ships in Europe. The same platform runs on top of HPE's GreenLake estate, NVIDIA reference architecture, Dell PowerEdge, mixed Supermicro builds, and the rack of whatever you already bought. We sell the AI layer above the iron, not the iron.
If your hardware runs Linux and reaches the network, it runs Eldric. The platform's job is to make the rack productive, not to dictate what the rack contains.
Sovereignty is not a marketing badge; it is an architectural property. Eldric runs entirely on the operator's hardware. There is no phone-home requirement. Licenses verify offline. Telemetry is opt-in. Cloud LLM backends are an option you choose, not a dependency you accept. Data residency is enforced by the federation layer: a tenant's region pins where their data lives, full stop. The AI plane is fully EU-built — kernel, modules, license server, vendor — so residency is a property of the architecture, not of a policy document.
For organisations that legally cannot ship their data across borders — healthcare under national rules, finance under regulatory mandate, defence under operational rules, public administration under sovereignty policy — the platform's posture is the platform's product. Eldric runs where your contract says it must.
Datacenter buyers do not deploy a "small cluster" the way they deploy a "big cluster" — the operational realities differ. Eldric uses the same software in every mode and changes only what is asked of it. A pilot starts on a single rack. The production rollout adds quorum and HA. The next office adds federation. None of the steps require a re-platform.
One to three U of compute. Pilot deployment, single team, single tenant. Available today.
Three nodes give you any-single-node tolerance with a clean majority vote. The most common production posture.
Workers split across racks or availability zones. Leader stays in a different zone. Rack-level failure is survivable.
HQ plus branches plus warm DR. Per-site autonomy; federation layer keeps directories and policy in sync.
The same RPM that runs on a developer's spare server runs on a fifty-node enterprise cluster. Scale is a configuration choice, not a procurement event.
An ISP offering "private AI" to enterprise customers, an MSP running shared infrastructure for several clients, or an internal IT department serving multiple business units — all need the same primitives: per-tenant capability tokens, quotas the cluster enforces, role-based access, and a license model that does not punish them for growing. Eldric ships all of this in one config schema.
| Tier | Scale | What it buys |
|---|---|---|
| Free | 1 controller · 1 router · 2 workers | Evaluation, proof-of-concept, small team. All daemons unlocked at a single-node scale; cluster features sized for pilots. |
| Standard | 1 · 2 · 3 | RAG, embeddings, agents, prompt database, custom models. Multi-tenant. The "we are using this for real" tier. |
| Professional | 2 · 4 · 10 | Dashboard, metrics, security extras, full RBAC, dual-controller. The mid-cluster production target. |
| Enterprise | 5 · 10 · 50 | High availability, orchestration, AI-decision routing, priority support, federation, named engineer. |
| Custom | unlimited | Source-code access, on-site deployment assistance, custom compliance certifications, air-gap installs. |
Every license is Ed25519-signed and verifiable offline against the embedded public key. Workers fall back to the local license file when the controller is unreachable — air-gap deployments do not need a heartbeat to a server. See pricing for cost and for enterprises for procurement.
A datacenter is not a greenfield. There is already a monitoring stack, a hardware management plane, a switch fabric, and a dozen other systems that need to keep working. Eldric's plugin host lets the LLM call any of them through the same tool surface — and lets the cluster operator add new ones without recompiling. SNMP for the legacy fleet. Redfish for modern servers. GreenLake and iLO for HPE estates. IoT and industrial protocols. Scientific data sources.
Plugins are sandboxed Python or JavaScript packages with a manifest, optional valve configuration, and a clear lifecycle. The plugin host enforces rate limits, error budgets, and per-tenant access. The catalog ships with the platform; customer-specific plugins live alongside Eldric's own. The plugin ecosystem is actively expanding — every quarter brings new entries to the catalog.
No build from source. No container orchestration to learn. No proprietary management plane to license separately. Eldric ships as a signed RPM, available from the Eldric package repository. Install on a Fedora, RHEL, Rocky, or Alma host, point the browser at the setup wizard, drop in your license, and you are running. Adding nodes is a one-line command on each one.
eldric setup command is available today. The browser-based setup wizard with network-hint admin GUI ships fully built in an upcoming 5.0.x patch.
curl -fsSL repo.eldric.ai/install.sh | sudo bash
A signed, GPG-fingerprint-pinned shell script. Adds the repo.eldric.ai dnf repository on Fedora 42+, RHEL 9+, Rocky, or Alma.
sudo dnf install eldric-aios
One package brings every daemon. The unit file enables and starts the kernel; node roles are configured next.
sudo eldric setup
The CLI subcommand waits for local health, activates your license, and prints an install summary. Subsequent nodes join with a cluster secret.
http://<host>:8880/chat
The single-node kernel listens on port 8880 by default — that's where the chat shell, controller dashboards, and the OpenAI-compatible API all live until you add a dedicated edge gateway in front (which is when the URL drops the port). First sign-up becomes admin. Configure tenants, models, knowledge bases. The cluster is in production.
For air-gapped installs, the same RPM repository ships on a USB key. The setup flow is identical; only the source of the package changes. See the install guide for the full walkthrough and install troubleshooting for the edge cases.
A platform that tries to be the right answer for everyone usually is not. Eldric is built for a specific kind of deployment: serious infrastructure teams who want a complete AI platform they fully control. That is a real audience, but it is not the only one. The right column below is just as honest as the left.
See how Eldric compares to Ollama, vLLM, NVIDIA NIM, OpenAI and the rest →
If you own the rack, the case is strong.
If infra is not your business, look elsewhere.
If you are in the right column, that is a useful answer too. We will tell you when a hosted service or a different tool is the better choice — including in the discovery conversation, before any contract.
A three-column ledger of where the platform actually is. Anything not in the leftmost column is not yet running in production — we will not pretend otherwise. The thing we promise is that this table will tell you the truth.
5.0 — shipping
Next 5.0.x patches — designed & dispatched
Later in 5.0.x — on the roadmap
Roadmap timelines change. Anything in the right two columns is genuinely planned and budgeted — but we will not promise a calendar quarter for software we have not finished.
Eldric is small enough that you can talk to the people who build it. A short conversation will clarify whether the platform fits your deployment, whether the timeline matches your need, and what a pilot looks like. No funnel. No self-service checkout. A real conversation.
For deeper audience-segmented positioning see For service providers, For enterprises, or For research institutions. For the architecture detail see Clustering & HA and How it works.