Lowest-friction consulting step

AI-Readiness Audit

A focused diagnostic when you need the path clarified before committing people to a build week or a full implementation sprint.

Mostly async, mostly Marc-led: map the context, source boundaries, ownership, access pattern, first proof use cases, and business case so the next step is clear.

Built by Marc Vallverdú — ex-COO of a 1,000-person commerce group, now leading its AI implementation: 40% less manual work across 50+ sites.

From £4,500 · Two weeks · Lower team-time commitment than Build Week · The audit fee you pay is credited toward the Company Brain Sprint if you continue. Bought the kit first? Its £299 is credited against the audit invoice.

Use this when the problem is real, but the shape is not clear yet.

Best for CEOs, COOs, VPs of Operations, Chiefs of Staff, and transformation leaders who can feel the scattered-context problem but should not commit a team to hands-on build work until the first team, source boundaries, access pattern, and owner model are clear.

How it runs: two weeks, mostly mine. Interviews with leadership and your heaviest AI users, a review of your tools, context, and current AI usage — then an executive readout that says whether the next step is internal DIY, Build Week, or the full Sprint.

AI is already in use, mostly in isolation

People keep pasting the same context into AI tools

Decisions are buried in meetings, tickets, Slack, and stale docs

Leadership expects leverage, but the gains are patchy

Why audit first

It de-risks the next build before anyone starts building.

The expensive mistake is not starting small. It is building the wrong brain: the wrong team, the wrong source systems, weak ownership, unclear permissions, or a proof use case leadership will not recognise. The audit decides the right build shape first — internal DIY, Build Week, or a full Sprint.

Which team or workflow should prove the first Company Brain

Which context belongs in the brain, which facts stay live, and what should never be ingested

Which access/runtime pattern is needed: existing AI tools, Slack, CLI, scheduled jobs, webhooks, or no persistent runtime yet

Who owns context quality, review, permissions, and write-back after the first build

What the audit does

01

Map the operating reality

Interview leadership and heavy AI users, separate useful workflows from experiments, and find the context people keep re-explaining.

02

Design the first sprint

Choose the first team, source-system boundaries, never-ingest list, access pattern, owners, and proof use cases before anything gets built.

03

Commit with confidence

Leave with the implementation plan, budget logic, and sprint-shaped first phase — with the audit credited if you continue.

What you get

Scored AI-readiness diagnosis across context, workflows, access, ownership, and governance

Current AI usage and context map

Top 3-5 AI/context opportunities

Source-system and company-context bottleneck map

Agreed never-ingest list and source-system boundary recommendations

Team, ownership, agent-access, and governance recommendations

Runtime readiness assessment: whether the first use cases need chat-based agents, CLI agents, scheduled jobs, webhooks, or no persistent runtime yet

Runtime boundary recommendation: what belongs in the Company Brain, what stays in source systems, and what — if anything — belongs in an agent runtime

Sprint-ready 30/60/90-day implementation plan

Executive readout with clear next steps

By the end, the first build is no longer fuzzy.

The context foundation. What company knowledge needs to become agent-readable first.

The first proof use cases. Where saved hours are visible and measurable without pretending the brain is just one workflow.

The missing layer. What access, curation, and ownership gaps are in the way.

The runtime question. Whether your next step is simply better brain access from existing tools, or whether a persistent company agent runtime — for Slack, Discord, CLI, webhooks, or scheduled workflows — would unlock the first real operating loop.

The next 90 days. What the sprint should build, who owns it, and how to measure progress.

The maths. The audit pays for itself if it prevents one weak automation build, one unused AI rollout, or one quarter of scattered experimentation.

If the Sprint is not next

The audit still does its job if it stops you building the wrong thing.

The audit is designed to de-risk implementation, not force one. If the work shows you are not ready for a full Company Brain Sprint yet, you still leave with the useful decisions made.

  • which team or workflow should go first
  • what context belongs in the brain and what should stay in source systems
  • what should never be ingested
  • who needs to own context quality and review
  • whether the next step is a Build Week, an internal pilot, or a later Sprint

That is the point of doing the strategic phase first: you avoid building the wrong Company Brain.

Not sure whether to start with the audit or the full sprint?

In 20 minutes, we’ll work out whether the first move is sprint discovery or a 30-day implementation.