Question 1

Where does AI pay back first?

Accepted Answer

Usually in high-volume, low-variance work that people currently do by reading: classifying incoming documents, extracting fields, drafting routine replies, summarising long records, answering repeated internal questions. These tasks have a measurable current cost and a tolerable error profile because a human still approves the output. We assess candidates with you during discovery and recommend starting with one where the payback can be measured, rather than a broad rollout.

Question 2

How do you handle our data?

Accepted Answer

Data handling is agreed in writing before any of it moves. We work with the minimum data needed, keep it within agreed regions and systems, and use commercial API terms that exclude your content from provider training where the provider offers that. Access is restricted and logged, and confidentiality is contractual. If a use case would require sending sensitive data somewhere you are not comfortable with, we design around it or tell you it is not worth doing.

Question 3

Should we build or buy?

Accepted Answer

Buy when a mature product already covers the workflow and your requirements are ordinary; the total cost is almost always lower. Build when the value comes from your own data, your own process, or an integration no vendor offers. Frequently the answer is a mixture: licensed models and platforms underneath, a thin custom layer where your business is genuinely different. We make that recommendation during the assessment, including when it means selling you less work.

Question 4

How is accuracy evaluated?

Accepted Answer

With a test set drawn from your own data and reviewed by someone who knows the domain. We agree what counts as a correct output, measure against that set before release, and keep the harness so changes can be re-measured rather than eyeballed. In production we monitor outputs, log failures, and keep human review on the paths where a mistake matters. Where a system cannot reach a usable standard, we report it plainly instead of shipping it.

AI Development

Deliverables

Six steps. No surprises.

Discover

Scope

Design

Build

Verify

Run

Frequently asked

Scope it with us.

An AI support agent that cut tickets by 70% for a fast-growing e-commerce brand

Sales automation that lifted lead-to-project conversion by 40% for a software services firm

An AI-automated delivery pipeline that cut development time by 45%