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Home / Platform / Assess
Platform

Assess: AI inventory and maturity, straight from the code.

Most organisations cannot say how many AI assets they run, let alone how mature each one is. Assess reads the repositories, discovers every model, integration, agent and call site, scores the project on six maturity lenses, and ranks the concrete steps that would raise the score most. It is the instrument behind the Assess phase of AIM.

Assess portfolio view
Why it exists

The Assess phase, measured from the code rather than the interviews.

An assessment built on workshops tells you what people believe is running. Assess reads what is actually running: which models are called from where, which agents exist, which configurations are live, and which of it is used at all. The maturity score is computed from evidence in the repository, and every recommended step points to the places in the code it applies.

Six lenses

Where a project stands, and what would move it.

Each lens is scored from evidence. Pick one and Assess shows what is going well, the next steps, and the lift each step is expected to add.

Observability

Are calls traced, are failures classified, is cost attributed?

Governance

Are intended uses documented, are keys separated, is there an approval path?

Security

Are tools scoped narrowly, are secrets managed, are inputs guarded?

Engineering

Is provider and model selection centralised, is there a test suite for behaviour?

Data

Is retrieval governed, is sensitive data classified, is lineage recorded?

Lifecycle

Are models versioned, are evaluations repeatable, is there a path to retire?

See it

Five screens from a live assessment.

From the portfolio sorted worst first to the ranked list of what to fix, this is what an Assess engagement produces in its first days.

Portfolio
226 AI assets across 4 projects, sorted worst first with the biggest issue per project
Where a project stands
The maturity ladder from Initial to Optimized, with per lens scores and the priority moves to the next level
Asset inventory
34 AI assets discovered and classified: models, LLM integrations, agents, configs and call sites, with usage status
Six maturity lenses
Observability, governance, security, engineering, data and lifecycle, each scored; pick one to see what is going well and the next steps with their expected lift
What to fix first
Ranked steps, biggest lift first, each naming the metric it raises and how many places in the code it applies
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Live captures from October 2026. Project names shown are from a pilot environment.

Where it sits

The first three weeks of AIM.

Assess runs in the Assess phase and feeds the ranked backlog that Implement starts from. The score gives the sponsor a baseline; the ranked steps give the pod its first fortnight of work.

Let's talk

Tell us the number you need to move.

A 45-minute working session with an operator who has run the kind of work you are describing. You will get an honest read on where your programme stands and what it would take to move it.