Run your own AI. Own every endpoint.
Browse open-weight models, deploy any of them to your GPU host in one click, fine-tune on your own knowledge, and watch the cost. All inside your bRRAIn — nothing proxied, nothing rented by the token.
No credit card required · Your endpoints, never proxied · Sovereign by design
Browse the open-weight catalog and deploy with one click.
Today you either rent intelligence or build a platform team
Running your own large language models has historically meant choosing between two bad options. LLMOps removes the trade-off.
Renting intelligence by the token
Commercial APIs bill you forever — a per-token tax on your own knowledge that compounds every single month you keep using it.
Your prompts and data leaving your walls
Every call to an outside model ships your most sensitive material across someone else's servers, governed by someone else's terms.
Needing an ML platform team to self-host
The alternative is hiring engineers to wrangle GPUs, containers, and pipelines by hand — SSH, terraform, and constant upkeep.
Discover, deploy, fine-tune, serve, and monitor — in one app
Paste a host key once, pick a GPU, deploy. No SSH, no terraform.
Deploy any open model to your own GPU host in one click
Browse the catalog of open-weight models, choose one, point it at your preferred GPU host or on-prem hardware, and ship — no infrastructure expertise required. You own the weights and the endpoint, so you stop paying a per-token tax on your own knowledge.
- One-click deploy from an open-weight model catalog
- GPU-host abstraction — bring your own host or run on-prem
- No SSH, no terraform-by-hand, no vendor lock-in
- Every endpoint is yours and private — never proxied
One dashboard for cost-per-token, p50/p95 latency, and drift.
See exactly what each token costs — and route to the cheapest model that clears the bar
A single dashboard tracks cost-per-token, p50/p95 latency, and drift across every model you run. Stop guessing at spend: watch it in real time and send each task to the model that meets your quality bar for the least money.
- Live cost-per-token across every deployment
- Latency p50 / p95 with drift alerts
- Compare models side by side and route by value
- Multi-host visibility — never captive to one cloud
Fine-tune on your own truth, then publish to the shared registry.
Train a model on your own knowledge — and every bRRAIn app uses it instantly
Fine-tune against your vault so the model speaks your organization's language and cites your sources, not a generic internet average. Publish it once to the bRRAIn LLM Registry and every app — Orchestrator, Document Portal, the memory engine — picks it up with no re-wiring.
- Fine-tuning grounded in your vault as ground truth
- Endpoints publish straight into the shared LLM Registry
- Every bRRAIn app consumes your models automatically
- On-device memory engine stays the always-on default
From open model to live endpoint in three steps
Browse open models
Search the catalog of open-weight models, filter by capability and size, and pick the one that fits the job.
Deploy to your GPU host in one click
Point it at your preferred GPU host or on-prem hardware and deploy — no SSH, no terraform, no platform team.
Every bRRAIn app uses it via the registry
The endpoint lands in your LLM Registry and is instantly available to every app, with cost and latency in view.
Put sovereign models to work
Stop renting intelligence
Replace recurring per-token commercial-API spend with open-weight models you deploy once and own — the savings compound every month you keep using them.
A private model for sensitive work
Stand up a model that never sees the public internet for legal, clinical, financial, or regulated workloads where data residency is non-negotiable.
Fine-tune on your own truth
Train a model against your vault so it speaks your firm's language, cites your sources, and reflects your decisions — not a generic internet average.
One registry, every app
Deploy a model once and serve it to every bRRAIn app and surface at the same time, with consistent cost and latency visibility.
Right-size your spend
Watch cost-per-token, p50/p95 latency, and drift across models in one view, and route each task to the cheapest model that meets the bar.
Multi-host resilience
Run across GPU hosts or on-prem hardware so you're never captive to one cloud's pricing or availability.
The full lifecycle — for under a quarter of the cost
Managed MLOps platforms charge a premium for the GPU plumbing, and commercial LLM APIs bill you per token forever. LLMOps gives you the full deploy-tune-serve-monitor lifecycle on infrastructure you already pay for — for less than a quarter of the comparable managed + per-token cost.
| Compared on | LLMOps on bRRAIn | Comparable platforms |
|---|---|---|
| Ongoing cost | Own the models; pay only for the GPU time you use | Per-token API fees and/or premium managed-platform markup |
| Data & weights | Yours — endpoints private, weights in your vault | Prompts and data leave your walls; weights rented |
| Setup | Point-and-click deploy — no SSH, no terraform-by-hand | ML-platform expertise or managed-service fees required |
| Reach | One registry feeds every bRRAIn app automatically | Per-app integration and separate billing |
| Lock-in | Open weights, portable across hosts and on-prem | Proprietary endpoints tied to one vendor |
| 5-year cost | Under 25% of the comparable approach | Baseline (100%) — and unbounded with usage |
"We moved our highest-volume workloads off a per-token API and onto two open models we deploy ourselves. Inference spend dropped by roughly 80%, and — the part legal cared about most — not a single prompt leaves our walls anymore."
Included with your bRRAIn — you only pay for GPU time
No per-token tax and no managed-platform markup. The whole deploy-tune-serve-monitor lifecycle comes with your bRRAIn — for under 25% of the comparable managed and per-token cost.
Deploy & Serve
- One-click open-model deployment
- Bring your own GPU host or on-prem
- Private endpoints in the LLM Registry
- Cost & latency monitoring
Fine-tune & Scale
- Everything in Deploy & Serve
- Fine-tuning + LoRA grounded in your vault
- Multi-host deployment & failover
- Drift alerts and per-model routing
- Under 25% of typical comparable cost
Sovereign Enterprise
- Everything in Fine-tune & Scale
- On-prem hardware support
- Role-tier governance & audit
- One registry across every bRRAIn app
Comparable managed MLOps platforms and per-token APIs typically cost several times more over the same period.
The honest answers
Do my prompts or data ever leave my walls?
No. The models run on your own GPU host or on-prem hardware, and every endpoint is private to your organization. Nothing is proxied through a third party, so even regulated and confidential workloads stay inside your sovereign boundary.
Am I locked into bRRAIn or one cloud vendor?
No. You deploy open-weight models whose weights you own, and they're portable across GPU hosts and on-prem hardware. You can run across multiple hosts for resilience, so you're never captive to one cloud's pricing or availability.
I don't have an ML platform team. Can I still use this?
Yes — that's the point. Deployment is point-and-click: pick a model, choose a GPU host, and ship. There's no SSH, no terraform-by-hand, and no containers to wrangle. The work that used to require a platform team becomes a few clicks.
How does the "under 25% of the cost" claim actually hold?
Managed MLOps platforms add a premium markup for GPU plumbing, and commercial APIs bill per token forever. LLMOps runs the full deploy-tune-serve-monitor lifecycle on infrastructure you already pay for — so you pay only for the GPU time you use, with no per-token tax and no managed markup.
Will it work with my GPU host?
Yes. LLMOps abstracts across major GPU hosts and on-prem hardware. Paste your host key once and your deployments target that host directly — bRRAIn never proxies the traffic or marks up the cost.
Stop renting intelligence. Start owning it.
Deploy your first open model, keep your data in-house, and watch the cost — all inside your bRRAIn.
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