Is AiRE consulting or implementation?

Both, weighted to implementation. The diagnostic is a short, structured piece of analysis, but everything after it is hands-on: deploying tools on your stack, enabling your teams, and putting governance in place. We are judged on what is running, not on what is recommended.

What stack do you work with?

Microsoft 365, SharePoint, Google Workspace, plus the AI platforms that fit your situation. We are model-agnostic: we pick the right model per problem rather than the one we are paid to recommend.

Do we need the £25k diagnostic first?

Usually yes. It is how we avoid selling you the wrong thing. Two weeks of structured analysis is far cheaper than six months of rollout pointed at the wrong problem.

What if the diagnostic says do not proceed?

Then you have spent £25k to avoid wasting £250k, and we will tell you what would change the answer. Sometimes the honest read is that you are not ready yet. We would rather say so than invoice you for the alternative.

How do you govern agents once they can act?

Every agent that can take an action gets an identity: a named owner, a scoped role, a registry entry and an audit trail of what it proposed, which policy applied and what it was allowed to do. Control sits outside the model, because prompt injection is the top LLM risk in the OWASP list and you cannot ask a model nicely not to be manipulated. We use least-privilege identity, tool allowlists and a policy layer in front of any privileged action, deployed inside your own tenant.

How does AiRE relate to Labs?

AiRE deploys AI through what you have; Labs builds what does not exist. When an AiRE Diagnostic concludes that the right answer is custom software, QuantSpark Labs takes over, starting with a working prototype in four to six weeks.

AiRE · AI Rollout Engine

Deploy AI through the organisation you already have

AiRE is the governed engine that takes you from AI experiments to AI operations.

Most agent pilots never reach production. That is an operating problem, not a model problem.

By 2026 the model is rarely the bottleneck. Value is won or lost in integration, governance, evaluation and the redesign of how work actually gets done. The numbers say the same thing.

84%

Deloitte

of organisations have not redesigned a single job around AI, so agents land on processes built for people. Deloitte, State of AI in the Enterprise 2026.

21%

Deloitte

have mature governance for agentic AI. Without owners, evals and an audit trail, a pilot cannot graduate. Deloitte, State of AI in the Enterprise 2026.

>40%

Gartner via Deloitte

of agentic AI projects are forecast to be cancelled by 2027, on cost, unclear value and weak controls. Gartner, cited by Deloitte.

~60%

BCG

of enterprises report minimal revenue and cost gains despite substantial investment. BCG research on AI value creation.

AiRE exists to close that gap. It treats a rollout as an operating problem: pick the right model per task, put controls and evals in before production, and give someone accountability for the result.

Who AiRE is for

Three situations we see again and again. If one of them is yours, AiRE was built for you.

Pilots that went nowhere

You have run pilots. Nothing stuck.

Pressure without a plan

The board wants an AI answer. The technology noise is deafening.

Capability gap

Your teams want to use AI properly, safely, and nobody owns the rollout.

How it works: two halves

AiRE has two halves. First we diagnose what is worth doing. Then we roll it out across the organisation you already have. You can stop after the diagnostic if the honest answer is to wait.

The AiRE Diagnostic

A paid, two-week assessment that ends with an honest read on every AI bet: roll out, build, buy, or wait. The free readiness diagnostic is the way in.

Readiness Diagnostic

Free3 minutes

Ten questions. A scored readiness band and an honest diagnosis. No follow-up unless you ask.

AiRE Diagnostic

£25kFrom 2 weeks

A short list of AI bets ranked by value, feasibility and risk, a recommended roadmap, and an honest read: roll out, build, buy, or wait.

Forward-deployed AI rollout

The delivery half. We embed alongside your teams and roll AI out across the stack you already run, taking you from AI experiments to AI operations. When the diagnostic says build, this is where the handover to Labs begins.

AiRE Rollout

From £8k/moOngoing

Fractional AI implementation across your existing stack. From AI experiments to AI operations.

Some of what we roll out

Sales enablement

AI rolled into your existing sales and revenue teams: meeting intelligence, lead scoring and deal sourcing inside the CRM they already use.

Knowledge and search

AI answers drawn from the documents and systems you already run, using AI in the flow of work.

Team enablement

Practical, role-specific AI adoption across functions, so the tools get used properly rather than sitting unopened after launch.

Governance and guardrails

The policies, controls and monitoring that let you scale AI use safely, with someone accountable for the rollout.

Weighing up who should run the rollout?

How to choose a forward-deployed AI partner

A governed rollout engine, not a one-off build

Nothing reaches production until it has earned it

AiRE moves each workflow through the same stages. Controls, evaluations and ownership are set before anything goes live, so the second workflow is faster and safer than the first: the engine carries over, not just the code.

Experiment

A workflow is tried against real data in a contained space, with no privileged access and nothing at stake.

Piloted

It earns a named owner, an evaluation set and a scoped role before real users touch it.

Production

A single use case goes live with monitoring, an audit trail and a defined stop mechanism.

Scaled

The next workflow reuses the same controls, evals and ownership, so it ships faster and safer than the first.

Built to be trusted with real authority

An agent that can act is a system with permissions. That is what makes governance and security part of the rollout, not an afterthought.

Every agent gets an identity, an owner and an audit trail

An agent that can act is an operating identity, not a feature. It carries a named owner, a scoped role and a registry entry, plus a record of what it proposed, which policy applied and what it was allowed to do. As Deloitte puts it, agents are neither capital nor labour, so they need governance built for neither. Governance is what lets you scale, not what slows you down.

Control sits outside the model

You cannot ask a model nicely not to be manipulated. Prompt injection is the top LLM risk in the OWASP list, and the dangerous form is indirect: instructions hidden in a document, email or tool result. The defence is least-privilege identity, tool allowlists and a policy layer in front of any privileged action. Credentials the agent never holds cannot be misused.

Sovereign by default, inside your tenant

Agents run inside your Microsoft tenant and against your systems, so data and tools stay in your perimeter. That lands with the regulated organisations we work with, where nothing sensitive should leave the estate to make an AI work.

The honest recommendation

A recommendation we are prepared to defend

Every AiRE Diagnostic ends with a recommendation we are prepared to defend: roll out, build, buy, or wait. Sometimes the honest answer is that you are not ready yet, and we will say so. We size run costs up front, not after go-live: McKinsey puts agent run costs well above the 10 to 20% of build cost typical of traditional IT, so some workflows should stay slower on purpose. When the answer is build, QuantSpark Labs takes over.

When the answer is build

Explore QuantSpark Labs