Most AI vendors ask you to send your data to their cloud. For a bank, a hospital, a government-adjacent operator or any company with a data-residency clause in its contracts, that ends the conversation before it starts.
We deploy the model where your data already lives: your data centre, your private cloud tenancy, or an isolated environment we build with you. Inference happens inside your network. Prompts, documents and outputs stay there. Nothing is sent to a third-party model provider unless you explicitly choose a hybrid setup.
What this covers
Deployment on your infrastructure
On bare metal, in your VMware or Kubernetes estate, or in your own AWS, Azure or GCP tenancy. You keep the keys and the network boundary.
Open-weight models, selected for the job
We size the model to the task and the hardware you have, rather than defaulting to the largest one. A well-scoped smaller model is usually faster, cheaper and easier to approve.
Retrieval over your own documents
The system answers from your contracts, policies and records, with the source shown. It does not answer from general training data when the question is about your business.
Access control that mirrors your organisation
Who may ask what, and see which answer, follows your existing roles. Every query and answer is logged for audit.
Evaluation before rollout
We define what a correct answer looks like with your team and measure against it, so the decision to go live rests on numbers rather than a demo.
Operations and handover
Runbooks, monitoring and an upgrade path. Your team can run it, or we do, under a support agreement.
Where we have done it
The same AI stack runs our own products.
TheMorph and Miter are production AI systems we built and operate ourselves. The retrieval, evaluation and guardrail layers we deploy for clients are the ones we run in our own products.
Security is where we come from.
Our founder spent over two decades running security programmes inside global corporations. Data-boundary questions are the first thing we design for, not an afterthought at review time.
How an engagement runs
- 01
Scope and data boundary
Which data the system may touch, where it is allowed to run, and which approvals it must satisfy. Written down before anything is built.
- 02
Architecture on paper
Model, retrieval, access control, logging and the hardware they need. You approve the diagram before the first line of code.
- 03
Build and evaluate
We build against your documents and measure quality on a test set your team agrees to.
- 04
Deploy and hand over
Installed in your environment, with runbooks and monitoring. Support is optional and contractual.
Start with a conversation.
Tell us what you are running today and what has to change. A founder responds directly.
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