Your team is already using AI.
Do you know where?
SAFE-AI give you a framework to build practices of discovery, information classification and security. Act before your most sensitive data ends up in the wrong AI model
Sound familiar?
Your board wants an AI strategy
by next quarter.
Most 5-to-500 person businesses face the same five problems with AI adoption. Koallabs gives you a structured, plain-English path through all of them — without a Big-4 invoice or a 90-page strategy deck you'll never read.
From scattered AI pilots
to a framework you can defend.
You don't need another tool — you need a way to make sense of the ones your team is already using, plus a plan for the ones they're about to ask for. That's what the SAFE-AI Framework delivers.
Where most SMEs are
A scattering of pilots. No policy. No one accountable.
Where SAFE-AI takes you
One framework. Five stages. Real governance, human-readable.
Know exactly where your business stands
on AI — before you spend a pound.
The AI Readiness Scorecard maps your organisation against the five pillars of the SAFE-AI Framework. You get a per-pillar breakdown, a plain-English analysis, and two or three quick wins you can action this week. No call required.
Every prompt is a data decision.
Most teams make it without thinking.
When your sales team pastes a customer email into a public model, or your ops lead asks Copilot to summarise an NDA — that's a data-classification event. SAFE-AI puts simple, auditable rules around the ones that matter.
If any of these are true for you, we can help.
We built SAFE-AI to solve familiar problems across telecoms, utilities, retail and professional services. The industry changes; the pattern doesn't.
Your team is using ChatGPT, Copilot or Claude — and no one has approved it.
Staff adopt tools faster than IT can evaluate them. You don't have a list, a policy, or a way to say "this one's fine, that one isn't" without sounding like the office of no.
Covered in Stage 1 · AssessCustomer data, source code, and IP are ending up in public models.
Nobody is doing it maliciously. They're drafting an email, summarising a contract, asking for a second opinion. The classification just hasn't been drawn.
Covered in Stage 3 · SecureGDPR was a marathon. ISO 42001 and the EU AI Act are queuing up behind it.
You don't need a 200-page compliance programme today. You need defensible baseline controls and a plan that will hold up when a client, auditor or insurer asks.
Framework mapped to NIST AI RMF & ISO 42001Three departments are piloting four tools, none of them talking to each other.
Budget is quietly leaking into overlapping subscriptions. Worse, nobody is measuring whether any of it is actually moving a business metric.
Covered in Stage 2 · StrategiseYou can't hire an AI governance lead. You won't pay Big-4 day rates.
You need something in between — someone who has done this across real SMEs, who speaks plain English, and who leaves you with a framework you can actually run yourself.
That's what we built Koallabs for"Am I allowed to use this for work?" is the most common AI question in the business.
Your team isn't trying to cause problems. They're trying to do their jobs faster and they want a clear, written rule to point at. "It depends" is not an answer that scales.
Covered in Stage 3 · Acceptable-use policyFive stages. One continuous Evolve loop.
SAFE-AI is a structured, five-stage methodology for secure AI adoption, built for organisations between 5 and 500 staff. Enterprise-grade thinking — without the enterprise price tag.
Assess
Understand what's already in use. Discover shadow AI. Baseline your current data & security posture.
Strategise
Rank use cases by impact & feasibility. Build a 30/60/90 roadmap sized to your team.
Secure
AUP, data-classification matrix and vendor-evaluation process — written in plain English.
Implement
Run managed pilots with guardrails, staff training and defined success metrics. No vanity dashboards.
Objectives
- Understand what AI tools are already in use — including shadow adoption
- Establish current knowledge-management-maturity & security posture
- Create a baseline grounded in evidence, not assumption
Key activities
- Stakeholder interviews across IT, ops, leadership & customer-facing teams
- Shadow-AI discovery — tools in use that were never formally approved
- Data-maturity review against structured criteria
Deliverables
- AI Readiness Report (per-pillar scoring)
- Shadow-AI register
- Quick-wins list — actions for the next 30 days
Start free. Move at the pace your business can actually absorb.
Three ways in. No lock-in, no annual contracts, no "transformation programme" marketing. Each step is a discrete piece of work with a defined deliverable.
AI Readiness Scorecard
A 7-minute self-assessment that maps you against the five SAFE-AI pillars.
- Per-pillar scoring vs. sector average
- Plain-English analysis
- 2–3 quick wins you can action this week
- No sales call required
Readiness Assessment
A guided, evidence-based diagnostic that produces a board-ready readiness report.
- 3–5 Stakeholder interviews
- Shadow-IT discovery
- Data-maturity & security posture review
- Prioritised 30 / 60 / 90-day roadmap
- Session to walk leadership through findings
Strategy, Roadmap and Guidance
Guidance Tailored to your SAFE-AI adoption needs
- Acceptable-use policy & data-classification matrix
- Vendor evaluation template & decision log
- Project Guidance and Team Training
- Quarterly Evolve reviews
Looking for clarification?
No hedging, no "it depends" — where we can give you a direct answer, we do. Where the honest answer is "it depends on your situation", we'll tell you that too.
Is SAFE-AI yet another certification we have to chase?
No. It's a working framework, not a certification. It's cross-mapped to other frameworks like NIST AI RMF, ISO 42001, TOGAF, COBIT and ITIL.
We already have a compliance team. Why would we need Koallabs?
A compliance team usually owns the rules. SAFE-AI covers the bit before that — the AI use-case inventory, the data-classification decisions, the actual policy wording your staff will read. It gives your compliance function something concrete to sign off.
How is this different from a Big-4 AI strategy engagement?
SAFE-AI cares about data, security and people. It gives your organisation the opportunity to adapt to and grow with AI capabilities.
Do we need to stop using AI tools while we figure this out?
No — and trying to would fail anyway. The Assess stage is explicitly designed to understand what's already in use. Governance gets layered on top of reality, not imposed over it.
What does "secure AI adoption" actually mean in practice?
Three things: you know what tools your people use, you've drawn a clear line around what data can go into which tool, and you have a defensible process for adding or removing tools when the market moves. That's it.
Seven minutes from now,
you'll know where you stand.
The AI Readiness Scorecard gives you a per-pillar breakdown and two or three things you can action this week — no call, no commitment.