# Engagement models

> Four ways to work with us. Each mode is deliberately scoped. Find where you are; the next step follows.

## AI Readiness

Before anyone writes code, we work out whether you are actually ready to build. If the basics
are not there, building is premature, and we will say so plainly. You leave knowing whether to
invest now, what to fix first, and what is really standing in the way.

**What we look for:** whether the data is there (available, clean, traceable, allowed); whether
you would know it is working; your security and governance footing; how well it fits the
systems an AI would touch; whether the work suits AI at all.

**What we deliver:** a readiness score, a gap analysis, a risk inventory, and a prioritized roadmap.

**Metrics that close it:** readiness coverage, critical-gap ownership, roadmap acceptance, time to decision.

## AI Foundation

For teams that know AI is coming but do not yet have anything underneath it. We build the
groundwork, document it end to end, and hand you a baseline you own, with a clear route to
building real things on top.

**What we look for:** where to start, your data and how it is reached, your platform today, who
takes it forward, and the regulatory/contractual/policy boundaries.

**What we deliver:** a way to measure quality; retrieval and grounding; guardrails and safety;
observability and tracing; governance and compliance; model and prompt management.

**Metrics that close it:** foundation coverage, time to a gated release, handover completeness, production readiness.

## AI Advisory

For a team that has started, or is about to, but has not built for production before. Senior
engineers in the room mean fewer wrong turns: the right calls get made sooner, and the wrong
ones get caught before your users feel them.

**What we look for:** how the system is put together, what you actually know about quality,
whether you can see in, how it holds up to misuse, and what stands between you and a safe launch.

**What we deliver:** a quality and grounding review, a guardrails and safety review, an
observability and tracing plan, and written production-readiness criteria.

**Metrics that close it:** decisions closed, risk-register reduction, iteration time, readiness at launch.

## AI Build

Two ways in. **Augmentation:** senior engineers join your team to accelerate the work and leave
capability behind. **Outsourced:** we plan it, build it, ship it, and hand it over. Either way you
end with a system in production that your team owns, not a black box you are afraid to touch.

**What we look for:** what "done" means, what it has to talk to, and the operating reality that
decides how we plan and where the risk sits.