AI Enablement · Secure by design

Adopt AI without opening a new attack surface.

Every business is being told to adopt AI. Almost nobody is being told how to do it safely. REDD treats AI the way we treat every other system that touches your data: secured first, governed properly, and rolled out so your team actually uses it.

ISO27001certified security foundation
24x7SOC watching your environment
E8ACSCaligned governance baseline

The part nobody mentions

Ungoverned AI is a data breach waiting politely

Staff are already pasting company data into free AI tools. The question is not whether your business uses AI. It is whether you control where your data goes when it does.

Shadow AI

Unapproved tools spread faster than any software in history. Without a policy and controls, your client data trains someone else's model.

Access sprawl

Copilot surfaces everything a user can touch. If your permissions are a mess, AI turns quiet over-sharing into instant exposure.

Compliance gaps

Insurers, auditors and government buyers now ask how AI is governed. An answer of "we trust our people" does not pass.

The REDD approach

Secure foundation first, tools second

AI sits on top of everything you already have. Build the layers in this order and it multiplies your team. Skip one and it multiplies your exposure.

1Layer 01 · foundation

Data and access, cleaned up

Permissions mapped and remediated before any AI tool sees them. What Copilot can reach, you decide first.

2Layer 02 · governance

Policy your auditor will sign

Approved tools, data boundaries and monitoring that proves the policy is followed rather than just published.

3Layer 03 · adoption

Tools your team actually uses

Copilot, automation and AI workflows deployed into real workflows, with training measured by usage rather than attendance.

Each layer rests on the one below. That is the whole point.

AI readiness check

Is your data ready for AI?

Copilot surfaces everything a user can already reach. These six questions show whether that is a productivity win or a disclosure incident waiting to happen.

REDD engineers working through a secure AI rollout with a client
AI readiness · governance · secure rollout

What your team gets

AI your people actually use

The gap between buying AI licences and getting value from them is training and workflow design. REDD deploys the tools inside the work your team already does, with the guardrails invisible until they are needed.

  • Microsoft Copilot deployed against clean, governed data
  • Automation and AI workflows built for your actual processes
  • Training that sticks, measured by usage rather than attendance
  • Ongoing monitoring from the same 24x7 SOC that guards the rest of your environment
Talk through your AI plans

Doing it properly vs doing it fast

Two ways to adopt AI

Both get you to Copilot. Only one of them survives an audit.

Switch it on todayThe REDD way
PermissionsInherited as-is, including the payroll folder shared in 2019Mapped and remediated before rollout
PolicyWritten after the first incidentSigned off before deployment, tested against real use
Shadow AIStaff keep using free tools quietlyApproved tools that are genuinely better than the free ones
Insurer questionNo documented answerEvidence pack ready
OutcomeProductivity gain, plus a new attack surfaceProductivity gain, on a foundation that holds

Scroll sideways to compare.

Common questions

AI enablement questions we get asked

Is Microsoft Copilot safe to roll out to our staff?

It is safe when your permissions are clean, and risky when they are not. Copilot respects existing access exactly, so it surfaces anything a user could already technically reach, including the payroll folder nobody realised was shared. REDD fixes the permission layer before deployment, which is the whole difference between a productivity gain and a disclosure incident.

What is shadow AI and why does it matter?

Shadow AI is staff using unapproved tools, usually free public chatbots, to get their work done. It matters because company data pasted into those tools may be retained and used for training, and because you cannot govern what you cannot see. The fix is not a ban that everyone ignores, it is providing approved tools that are genuinely better than the free ones.

Do we need an AI policy?

Yes, and increasingly you will be asked to produce it. Insurers, auditors and government buyers now ask how AI use is governed. A workable policy names approved tools, sets data boundaries, and defines what must never be pasted into a model. REDD writes one your auditor will accept and your staff will actually follow.

How long does an AI readiness assessment take?

The assessment itself is typically two to three weeks depending on tenant size. You get a report covering access and permission exposure, data classification gaps, and a prioritised remediation plan with indicative effort. Many businesses stop there for a quarter and fix the foundations before rolling anything out.

Will AI replace our staff?

Not in the deployments we run. What it reliably removes is the repetitive work around the edges: summarising, drafting, formatting, searching. The productivity gain shows up when people stop hunting for information and start using it, which is a training and workflow problem more than a technology one.

What does AI enablement actually cost?

There are two components: the readiness and governance work, which is a defined project, and the licensing, which is per user. Most clients find licensing is the smaller surprise. The bigger variable is how much permission remediation the readiness assessment uncovers, which is exactly why we assess before quoting the rollout.

Start with the readiness assessment

Thirty minutes with a REDD engineer. You will leave knowing exactly what AI can safely reach in your environment today, and what needs fixing before it should.

Get in touch

Tell us what is running your business

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