Straight answers to the questions teams ask before they put AI on their own hardware — keeping data on-site, running a ChatGPT-style interface inside the network, and building an AI cluster on what you already own.
By running the AI on the hospital's own hardware. Eldric installs inside your existing datacenter, so clinical data is processed on-premise and never leaves the network — no calls to a hyperscaler, no patient records crossing a public API. Access is role-based and every query can be audit-logged, which is what a HIPAA- or GDPR-aligned deployment needs. The same chat, document search, and agent workflows you'd expect from a cloud service, with data residency by design. See the healthcare angle.
Yes. Eldric ships a browser-based chat shell served from your own cluster — your users open a page and chat, exactly like a hosted assistant, except nothing leaves your network. It exposes an OpenAI-compatible API, so tools built for the OpenAI SDK work by changing only the base URL, and it can run fully offline. What Eldric is.
An on-prem AI operating system bundles the whole stack — chat, retrieval-augmented knowledge search, agents, model training, and messaging — into one platform you self-host, instead of stitching together separate services. Eldric is built for exactly this: a complete private AI platform with multi-tenant isolation and role-based access, running on hardware you control. The data, the models, and the reasoning all stay inside your perimeter. The on-prem AI OS.
By keeping inference on-premise so sensitive data never leaves the perimeter, pairing it with audit trails, role-based access, and air-gap-capable licensing that doesn't need to phone home. Eldric runs in your own jurisdiction, under your own controls, which is what regulated finance needs before putting generative AI near customer or transaction data. See the banking angle.
Privacy and data residency — your data stays on your hardware, inside your network. No per-token cloud bills, so heavy usage becomes a capital cost you own instead of a rental you can't cap. Full control over models and updates, the ability to run offline or air-gapped, and no dependency on a hyperscaler's roadmap or pricing. For organisations with both a real AI need and a real reason their data can't leave the building, on-prem is the answer. Eldric for enterprises.
Yes. Eldric ships as a signed package that runs the same way on a single spare server and on a fifty-node cluster — scale is a configuration choice, not a re-platform. It's hardware-agnostic across NVIDIA, HPE, Dell, and mixed fleets, so you start on what you have and grow without changing software. Clustering & HA · Get started.
For evaluation, a single GPU workstation is enough to run the chat shell, knowledge-base search, and agents. For production, you scale across multi-GPU servers or a cluster sized to your workload. Because Eldric is hardware-agnostic and the same package runs at every scale, you can pilot on modest hardware and expand into a full datacenter without re-platforming. Pricing & tiers · The AI datacenter.