Independent intelligence.
Private AI, built on infrastructure you control. We select, deploy and optimise open-weight models in your cloud or on your own hardware.
01 / THE INFRASTRUCTURE
Your prompts, documents and responses stay in your environment. Choose where it runs. We make the pieces work together.
WHERE YOUR MODEL RUNS
Deploy in AWS, Azure or Google Cloud. You hold the account, control access and pay your provider directly.
Your data centre. Any site with Linux servers, NVIDIA GPUs and the network access you choose. No cloud region involved.
Example regions. GPU availability varies by provider and region; we confirm it before provisioning.
Model weights, prompts and outputs stay in this region.
Models selected for your tasks, with licence terms reviewed.
Hardware sized to your model, context length and traffic.
Your accounts, credentials, configuration and documentation.
02 / THE ENGINEERING
Start with a private model. Add the knowledge, integrations and performance your team needs.
Open-weight models. Right-sized GPUs. A secured endpoint, running in your environment.
Explore deploymentRetrieval over your company documents, with answers that point back to their sources.
Evaluate candidates on your real tasks. Understand quality, hardware and cost before you commit.
Tune batching, memory and multi-GPU serving. Measure the difference against your baseline.
Connect your model to the applications, data and tools your team already uses.
Optional monitoring, model upgrades and capacity reviews. Support on your terms.
Measured on your workload. Hardware, precision and test conditions documented. Running costs estimated before provisioning.
03 / THE DEPLOYMENT
A clear scope. A fixed implementation fee. A working system your team can take over.
Let’s talk about your use caseWe learn the use case, data sensitivity, expected users, latency needs and where the system must run.
You receive a recommended model, hardware configuration and running-cost estimate, with the reasoning behind each.
A written scope with deliverables, acceptance criteria and a fixed implementation fee.
We deploy into your environment and test against the agreed criteria, documenting the conditions of every test.
Documentation, credentials and a walkthrough for your team. Continue with our support, or run it yourselves.
04 / THE ENGAGEMENT
One-time implementation. Infrastructure billed to your own account. Ongoing support when you want it.
One model, one environment, a validated endpoint.
Fixed fee. Quoted to scope.
Discuss FoundationBuilt for real users, with retrieval and integration.
Fixed fee. Quoted to scope.
Discuss ProductionMultiple models and teams on shared infrastructure.
Fixed fee. Quoted to scope.
Discuss PlatformA CLEAR VIEW OF THE COST
Covers the scoped work: recommendation, deployment, validation and handover. Agreed in writing before work starts.
Cloud GPUs, storage and networking, or your own hardware. Billed to your account. We estimate it up front.
Monitoring, upgrades, patching and capacity reviews. Not included in the implementation fee.
05 / THE HANDOVER
Everything you need to operate the deployment is handed over. Your system keeps running independently of InferenceWorx.
Infrastructure is provisioned in cloud accounts or on hardware you own. Billing goes to you.
Access credentials are handed over and rotated at handover. We retain no access unless you grant it for support.
Deployment configuration, scripts and documentation are delivered to your repository.
Models with published weights, chosen with their licence terms reviewed against your intended use.
Private infrastructure. Documented security controls. See how we build it
A FEW MORE THINGS
A model whose trained weights are published, so it can be downloaded and run on your own infrastructure. Licence terms vary between models; we check them against your intended use as part of selection.
Yes. The implementation fee is fixed and agreed in writing before work starts. It does not include hosting or ongoing maintenance. Infrastructure is billed by your provider, and ongoing support is optional and priced separately.
No. Models run in your cloud account or on your own servers. That keeps your data in your environment and means you are never dependent on us to keep the service running.
AWS, Microsoft Azure and Google Cloud, GPU cloud providers, and on-premise Linux servers with NVIDIA GPUs. If you have a different environment in mind, tell us about it and we will say plainly whether it is a good fit.
It depends on the task. For many focused business tasks, well-chosen open-weight models perform well; for others, they may not match the largest commercial models. That is why we evaluate candidates on your own examples before recommending one.
Not on its own. Self-hosting gives you control over where data goes, which can support your security and compliance work. We implement specific controls (network isolation, encryption, access control, logging policy) and document them so your team can assess them against your own obligations.
Every figure comes with its test conditions: model and precision, hardware, prompt and output lengths, concurrency level and the tool used. Customer-specific requirements are validated before we commit to a configuration.
It depends on scope and on how quickly infrastructure access can be arranged. You will get a timeline with the quote, once the requirements are clear.
Yes. We also build custom AI services (document processing, classification, extraction, agents and workflow automation), usually on top of a private deployment. Tell us what you are trying to achieve.
LET’S BUILD SOMETHING
Tell us what you want to run. We’ll work out the model, the machines and the path to production.
hello@inferenceworx.comYOUR NEXT DEPLOYMENT STARTS HERE