Question 1

We’re not sure where to start with AI. Is that a problem?

Accepted Answer

It’s the normal starting point. The readiness assessment exists precisely for this: in two to three weeks you get a ranked list of use cases with feasibility and return estimates - including, sometimes, the recommendation to wait. You’ll know what to build first and what it should cost.

Question 2

Can our data stay private?

Accepted Answer

Yes. Depending on your requirements we deploy on your cloud accounts, use enterprise API agreements with zero-retention terms, or run open-weight models on infrastructure you control. Data residency and privacy constraints shape the architecture from the first discussion.

Question 3

How do you keep AI systems from embarrassing us?

Accepted Answer

Evaluation before deployment: every system ships with a test suite of real cases from your domain, measured for accuracy, groundedness, and tone. In production, outputs are monitored, low-confidence cases route to humans, and behavior changes are caught by regression runs - the same discipline as any other software we ship.

Question 4

Which AI models do you use?

Accepted Answer

The one the evidence supports for your use case. We work with commercial frontier models (Anthropic, OpenAI), open-weight models (Llama, Mistral) for private deployments, and often a mix - a smaller model for volume work with a frontier model for hard cases. Model choice is an engineering decision we revisit as the landscape moves.

AI that survives contact with production.

What this covers

AI Strategy & Readiness Assessments

Generative AI Implementation

Asked before every engagement

Find out what AI can do for your business