Services & Framework
An assessment that produces evidence, not a slide of aspirations.
Every engagement runs on the same structure: a consultant-led readiness assessment across seven operational lanes, a maturity read on each lane independently, and a roadmap that names exactly what has to be true before the next stage is credible.
We typically reply within 1–2 business daysTwo paths, not two equals
Enhancement is the default. Offering is the exception.
We don’t start every client on a hunt for an AI product. Most transformation value shows up as AI making existing operations cheaper, faster, higher-quality, or lower-error — not as a new AI-branded revenue line. Our framework builds that priority in explicitly.
Enhancement
AI improves how the business already runs. This is the expected path for most clients, and the one we lead with in every assessment.
- Named process, named metric, before/after evidence
- Cost, speed, quality, or error-rate improvement — measured, not asserted
- Assessed against a recovery-window test: could the business revert to the old way, and at what cost?
Offering
AI becomes a customer-facing product or revenue line. A valid path for some clients — but a minority case, not the framing we open with.
- New AI-enabled product or feature, live with customers
- Adoption or revenue attribution named directly, not projected
- Only credible once the underlying use-case and technology maturity can support it
The 7 lanes
What each lane answers
Two lanes (Data and Technology) are parallel enablers, not sequential steps. Process redesign lives in Governance; human change management lives in People — so the same evidence never inflates two lanes at once.
Leadership & Strategy
Is there executive vision, commitment, and investment for AI?
People & Skills
Can the workforce understand, adopt, and build with AI?
Data
Is data accessible, quality, governed, and AI-ready?
Technology & Tools
Are there platforms, infrastructure, and tooling to deploy AI?
Use Cases & Value
Is AI applied to real problems, with business impact measured?
Governance, Process & Risk
Is AI controlled responsibly, and is work redesigned around it?
Operating Model & Scale
How is AI organized, sustained, and scaled across the enterprise?
The maturity model
Six stages per lane, Stage 0–5, scored independently
Each lane is scored against its own mandatory evidence — not averaged into a single company-wide number. A company that has scaled Use Cases past Governance sees that gap surfaced as a flagged risk, not smoothed over by a composite score.
Floor
Informal
Committed
Structured
Scaling
Evidence-Led
Stage names vary by lane — shown here in general form. Stage 0 is a genuine floor with nothing to check; by the time a company is in a readiness conversation with us, they’ve almost always already left it. Stage 5 in every lane is defined by an operational mechanism that can be verified in an interview, not a state-of-being claim like “AI is simply how we work.”
The gate system
Progress is dependent, not parallel
Lanes don’t mature in isolation. A set of hard and soft gates encodes the real dependencies between them — for example, production AI can’t be credited without people trained to run it, and scaling can’t be credited without governance in place first.
Hard gates
Cannot proceed without the prerequisite. These block a stage from being scored at all until the dependency is met — e.g., production use cases require both trained people and a governance baseline.
Soft gates
Can proceed, but flagged as risk. These surface the pattern of “you’ve scaled faster than your foundations” without hard-blocking a client’s progress.
Engagement model
Advisory-led. Implementation-backed.
Assessment
Consultant-led interviews across the relevant lanes — typically 3–4 active lanes at a time, not all seven at once. Self-serve surveys aren’t used: self-reported maturity is reliably inflated, especially on soft dimensions like leadership and governance.
Roadmap
A prioritized, gated plan showing what has to be true — by lane — before the next stage is credible, with the enhancement path (Path A) as the lead recommendation unless the evidence points elsewhere.
Implementation
Hands-on delivery via a nearshore team: tooling, integrations, and process redesign. Training delivery is available depending on scope.
Questions
Frequently asked
Most maturity models are self-assessed — a leadership team fills out a questionnaire and grades itself. Ours is consultant-led: interviews across seven operational lanes, scored against named evidence, not self-reported confidence. Self-assessment reliably inflates scores, especially on soft dimensions like leadership and governance.
No. Most organizations we talk to are early on most lanes, and that’s normal. The assessment exists to tell you exactly where you stand and what’s realistically next, not to gatekeep who gets to start.
It depends on how many lanes are in scope. Most engagements focus on 3–4 active lanes rather than all seven at once, since that’s usually where the real constraints are. We scope timing specifically for your organization in an initial conversation.
No — that’s the exception, not the default. Most recommendations are about improving how you already operate: cost, speed, quality, error rate. A product or offering recommendation only comes up when the evidence actually supports it.
Latin America is our initial focus market, with Europe next. If you’re outside both regions, reach out anyway — we’re happy to talk about fit.
Ready to see where you actually stand?
We’ll walk you through what the assessment covers and which lanes are most likely to matter for your organization.