On-Premise LLM Deployment in Charlotte
The best On-Premise LLM Deployment in Charlotte, at the best available price.
You have the GPU and you have the model. What is missing is the leg in between: the model exposed as a reliable private API, reached securely from your application, returning data you can trust. That is the whole engagement.
Charlotte is the second-largest banking centre in the US, home to major bank headquarters and large operations of others, with a growing fintech scene around them. Much of the software demand comes from banks, their vendors and the startups selling to them, so vendor risk reviews shape almost every project.
A Charlotte bank's third-party risk team will ask where data goes and who can see it. A model running in the bank's own cloud account, or a vendor's dedicated environment, answers both without a new subprocessor.
What you get
- vLLM serving tuned to your GPU: quantisation on the native kernel path, KV cache sizing, continuous batching, prefix caching
- A private network path with no public exposure, verified as a direct peer connection rather than a relay
- Schema-constrained responses plus a deterministic QA gate, so a wrong answer is rejected rather than rendered
- Documented baseline: tokens per second, time to first token, real concurrent capacity
- Infrastructure as code in your repository, a runbook, and every credential held by you
No upfront payment and no escrow required. You hold every dollar until a checkpoint is delivered and accepted, and thirty days of defect correction is included. Scope and price are set on a call.
Invoiced in USD, payable by Wise or bank transfer.
Request a callback
You speak to the engineer who does the work. No sales rep, no deck.
Who builds here
On-Premise LLM Deployment
Charlotte's banks and the vendors selling to them need AI that passes third-party risk and model risk reviews, and a model inside the bank's own environment is the cleanest route.
What Charlotte companies build with us
Get it built at $0.
That is not a discount. It is when you pay. The work is split into checkpoints with acceptance criteria written down before anything starts, and each checkpoint is invoiced only after you have seen it and accepted it. No deposit.
- $0 to start
- You hold every dollar until a checkpoint is delivered and you accept it. No approval, no invoice.
- Fixed cost, unlimited features
- Or hire the team outright: one fixed monthly cost, unlimited feature development, any stack.
- The engineer takes your call
- The person on your first call is the one who architects and writes it. No account managers, no bench time.
A US agency quotes $50,000 to $150,000 for the same build and asks for 40 to 50% of it before a line is written. Account managers, project managers, sales commission and bench time. None of it appears in your product.
Three stages, nothing hidden.
Fixed-fee assessment
Five business days from the day access is in place. Your stack examined end to end, existing work classified as preserved or replaced with reasons, the connection design, and acceptance criteria written as testable statements.
Implementation in checkpoints
Around three weeks. Each checkpoint has written acceptance criteria agreed before work starts, and is invoiced only after you accept it. Appoint an independent technical reviewer if you want one.
Handover and closeout
One real request through your real application, on synthetic data, passing every QA rule. Runbook, recorded handoff, and all our access removed with written confirmation.
What actually applies here.
Regulation and data
Banks follow the federal banking regulators' interagency guidance on third-party risk management, issued in 2023, which shapes the due diligence, contracts and monitoring they require of every technology vendor. Model risk management guidance means any AI used in a bank's decisions needs documented validation and oversight. North Carolina has no comprehensive consumer privacy law yet, so federal financial privacy rules and the state's breach notification law do most of the work.
Contracting and payment
You contract with an individual consultant based in India rather than a US entity. Invoices are issued in USD and paid by Wise or bank transfer, with no payroll and no benefits load on your side. Whatever documentation your finance team or counsel needs from an overseas contractor is provided before work starts.
Working hours
Four or more hours of daily overlap with Eastern time, calls in your morning, and same-day replies on working days.
Can you help us pass a bank's third-party risk review?
Yes. We build the controls they ask about, such as access logging, encryption and incident response, and help prepare the documentation. Formal certifications such as SOC 2 come from an auditor.
What does model risk management mean for an AI feature?
Documenting what the model is for, its limits, how it was tested and how it is monitored, with a person accountable for it. We build those records alongside the feature.
We already have hardware and a model running. Is that a problem?
It is the ideal starting point. Existing work is classified during the assessment as preserved unchanged, preserved with changes, or replaced, with reasons, and nothing is replaced without your written agreement.
Can it be fully air gapped?
Yes, including model and dependency mirroring, offline updates and local evaluation, with no outbound network access at all.
Who holds the accounts?
You do, throughout. Cloud accounts are created and held by you, our access is named and limited-privilege, and it is removed at handover with written confirmation.
Private LLM Infrastructure
Self-hosted LLM deployment on hardware you own. vLLM serving, private networking, validated output.