/ ai infrastructure
SCM Resource designs, builds and operates GPU servers, model access and AI agents for companies taking AI from prototype to production.
/ the gap
A prototype runs on one API key and a company card. Production has other ideas. Traffic doubles without warning, one contract clause decides where data may live, and the monthly bill climbs faster than usage. We build the layer underneath all of that, and we stay to run it.
01
Current-generation accelerators are allocated months ahead. Teams that start looking on the day they need GPUs join the back of the line. We work with hardware suppliers continuously, so lead times are known before you commit and a node you order is a node that arrives.
02
Per-token pricing is ideal for experiments and painful at volume. Past a certain level of steady traffic, reserved or owned capacity costs less per million tokens, and the difference compounds every month. We show you where that line sits for your workload before you cross it.
03
Customer records, contracts and source code often cannot be sent to a third-party endpoint. Serving models inside your own network settles the question at the architecture level. Security reviews get shorter, and legal stops being the bottleneck.
/ the stack
Most companies buy hardware from one vendor, cloud from another, model access from a third and automation from a fourth. When something breaks, four support desks point at each other. We deliver the whole path from silicon to agent, so every problem has exactly one owner.
/01 servers
Current-generation NVIDIA and AMD accelerators, high-memory CPU nodes and NVMe storage. Every build is sized against your models, batch sizes and context lengths before a single part is ordered, so you pay for the memory and bandwidth the workload actually uses.
/02 compute
Low-latency fabric, shared storage and a scheduler your engineers already know. Train, fine-tune and serve on the same footprint, move capacity between jobs by policy, and add nodes without re-architecting.
/03 models
Frontier APIs and open-weight models behind a single endpoint. Keys stay on the server, usage is metered per team, and moving to a new model is a configuration change. Your developers write against one API for the life of the product.
/04 agents
Support, lead follow-up and back-office agents wired into your inbox, CRM and documents. They run on hardware you control, follow written policies, and hand the conversation to a person when they should.
/ inside a node
Before a node ships it runs burn-in under full load. Anything that throttles, drops a link or throws a memory error goes back to the bench. You receive the test logs with the delivery note.
/ model gateway
Applications talk to a single OpenAI-compatible API. Behind it, the gateway decides which model answers, charges the call to the right team, masks what should not leave, and writes a log line you can hand to an auditor. Switching providers is a routing change. Nobody rewrites the application.
your applications
Support desk Sales CRM Internal search Product featuresscm gateway
models
Claude api GPT api Gemini api Llama self-hosted Mistral self-hostedPOST /v1/chat/completions
Authorization: Bearer team_support_••••
{
"model": "auto:balanced",
"messages": [{ "role": "user",
"content": "Where is order 58213?" }]
}
→ routed to llama-3.3-70b · self-hosted · 412 ms
→ 0 bytes left your network · billed to: support/ agents
An agent that talks to your customers is an employee you never interviewed. So we scope each one like a role: what it may read, what it may change, when it must hand over to a person, and how every step is recorded. Then it runs on the same infrastructure as the rest of your stack.
support
Answers order, account and product questions from your knowledge base and live systems. Escalates refunds, complaints and anything below its confidence threshold, with the full context attached.
revenue
Replies to inbound enquiries within a minute, qualifies them against your criteria, books meetings into the right calendar and updates the CRM without anyone copying and pasting.
operations
Reads invoices, purchase orders and forms, checks them against your records, flags mismatches and prepares entries for a person to approve.
channels · email · web chat · whatsapp · telegram · slack · microsoft teams
/ operations
Every node reports temperature, power draw, memory errors and interconnect health every few seconds. Alerts go to an engineer who knows your setup. Each month you get a short report covering what ran, what failed, what we changed, and how much capacity you will need next quarter.
/ deployment
Where the hardware lives is a business decision before it is a technical one. It depends on your data rules, your load pattern and how much of the operation you want to own. We build all three and help you choose with numbers on the table.
Hosted
Dedicated hardware in a professional data centre, run by our team. You get root access, private networking and a named engineer. Nothing is shared with other customers.
Fits: teams that want capacity without a facilities project.
On-premises
We deliver, rack and commission the servers in your facility, then hand over the keys or keep operating them for you under a service agreement.
Fits: regulated data, existing server rooms, steady long-term load.
Hybrid
Steady workloads on your own servers, peaks on ours, and one model gateway in front of both so applications never notice where a request was served.
Fits: seasonal traffic and fast-growing products.
/ process
Four stages, each ending in something you can read, check and sign off. At every point you know what was decided, what it costs and what happens next.
We profile your models, prompts and traffic, then write a build sheet with the monthly cost and the cost per million tokens for each option.
you receive · workload profile · build sheet · cost model
Hardware is sourced, assembled and burned in under full load. You see the test logs before anything leaves the bench.
you receive · burn-in logs · rack elevation · acceptance checklist
Racked, networked and loaded with your serving stack, model gateway, agents and monitoring. Acceptance tests run on your real traffic.
you receive · serving stack · gateway config · runbooks
Round-the-clock monitoring, a capacity review every quarter, and an engineer who knows your setup by name.
you receive · monthly report · capacity forecast · on-call engineer
/ security
We would rather answer them in the architecture than in an incident review. These controls ship with every deployment. None of them is an upgrade tier.
01
Inference and training run in private subnets. Nothing is reachable from the internet unless you decide to publish it.
02
Provider keys live in a secrets manager on the server side. Applications receive scoped team keys that can be revoked in one step.
03
Every model call records who made it, which model answered, token counts and latency. Prompt bodies are stored only if you switch that on.
04
Single sign-on for consoles and dashboards, role-based permissions, and separate duties for operators and approvers.
05
You decide how long logs, prompts and outputs are kept. Deletion runs on a schedule and leaves a record that it happened.
06
Each server is tracked by serial number from delivery to decommissioning. Drives are wiped to a documented standard or destroyed on request.
/ where it fits
Document review, onboarding summaries and analyst copilots, served inside the firm’s network with every call logged.
Clinical note drafting and literature search on private infrastructure, with patient data kept away from third-party endpoints.
Product copy, search, recommendations and service agents sized for peak season rather than an average Tuesday.
Contract comparison and research assistants grounded in the firm’s own precedents and templates.
Visual inspection, maintenance manuals and shipment exception handling running close to the operation.
Model-backed product features with predictable unit costs, and a gateway that lets product teams change models freely.
/ what runs on it
/ house rules
/ faq
If yours is not here, send it over. An engineer answers, not a sales script.
No. You can rent dedicated capacity from us by the month, buy servers outright, or combine the two. The build sheet puts the cost of each path side by side over one and three years, so the decision is made on numbers.
Any open-weight model that fits the hardware, including Llama, Mistral, Gemma and their fine-tunes, plus frontier APIs such as Claude, GPT and Gemini through the gateway. Most customers end up using several, routed by task.
Mostly it depends on hardware lead times. Hosted capacity on hardware we already operate is the fastest route. Custom builds take longer, and you get a dated plan before you sign anything.
Yes. Many teams begin with the gateway alone, pointed at external APIs, and move steady workloads onto dedicated servers once the traffic pattern is clear. Nothing built in the first phase is thrown away.
You do. Weights, adapters, datasets and logs produced for you are yours, and they are exported in standard formats if you ever leave.
An engineer is paged directly. Faulty nodes are drained from the pool first and repaired second, so traffic keeps flowing while the fix happens. You get a written incident note the next morning.
Yes. The gateway and agents can run in your cloud account, on our servers, or both, and they connect to the identity provider and monitoring tools you already use.
/ contact
Send the model, the traffic and the deadline. An engineer replies with a first build sheet.
Contact@scmresource.com