Will our data be used to train someone else's model?

That depends on the provider and plan, and it is something we establish in writing before building. Enterprise API tiers from major providers generally exclude training on customer data. We confirm the specific terms rather than assuming.

How accurate will it be?

Accuracy depends on the task and the quality of the underlying content. We build an evaluation set from real examples so accuracy is measured rather than claimed, and we design the interface to make uncertainty visible.

Can it run on our own infrastructure?

For some use cases, yes — open-weight models can be self-hosted where data residency requires it. There is a real trade-off in capability and operating cost, which we will set out before you decide.

Artificial Intelligence

AI that is grounded in your business.

We build AI features that are connected to your actual data and processes, with the evaluation and guardrails needed to trust the output.

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Why this matters

Most disappointing AI projects fail for the same reason: the model was never connected to the organisation's real information, or nobody defined what a correct answer looked like. We start with the task and the evaluation criteria, then build the retrieval and guardrails that make the output dependable enough to act on.

Where AI earns its place

Internal knowledge assistants
Answering questions from your documentation with citations.
Document processing
Extracting structured data from unstructured files at volume.
Content support tools
Drafting and summarisation inside an editorial workflow.
Customer support augmentation
Suggested responses and triage with a human in the loop.
Classification and routing
Sorting incoming work reliably enough to act on automatically.

How we build responsibly

Retrieval grounded in your own content, with sources shown
Evaluation sets defined before launch, not after complaints
Human review on consequential decisions
Access control so the assistant respects existing permissions
Clear handling of what happens when the model does not know
Data handling agreed explicitly before anything is sent to a provider

Questions

Frequently asked questions

: That depends on the provider and plan, and it is something we establish in writing before building. Enterprise API tiers from major providers generally exclude training on customer data. We confirm the specific terms rather than assuming.
: Accuracy depends on the task and the quality of the underlying content. We build an evaluation set from real examples so accuracy is measured rather than claimed, and we design the interface to make uncertainty visible.
: For some use cases, yes — open-weight models can be self-hosted where data residency requires it. There is a real trade-off in capability and operating cost, which we will set out before you decide.

Related services

Build AI features people actually trust the output of.

Tell us about the project and we will come back with a considered approach, not a template proposal.

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Why this matters

Where AI earns its place

Internal knowledge assistants

Document processing

Content support tools

Customer support augmentation

Classification and routing

How we build responsibly

Frequently asked questions

Related services

Build AI features people actually trust the output of.